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3rd International Conference on Universal Threats in Expert applications and Solutions, UNI-TEAS 2024

作者： Bhargava, Ritu Dixit, Pooja Rathore, Pramod Singh Goswami, Ankur Ajmer India Department of Computer Science Dezyne College Ajmer India Department of Computer and Communication Engineering Manipal University Jaipur India Department of Computer Applications Governmentt Engineering College Bikaner India

ISBN: (纸本)9789819751457

Paper deals with the predictive apriori algorithm for a disease related to hemoglobin blood test data. The dataset has been collected from public dataset. The dataset was pre-processed to remove missing and unwanted data. In this paper, Boolean matrix is defined for eliminating the candidate from the subset, which is not frequent. In the Boolean matrix, frequent patterns are generated using "AND" operation. Since the anemia is a common health problem which affects mostly women worldwide. The approach is used in this paper for detecting the anemia disease from the result investigation. Predictive apriori algorithm and Boolean matrix give the better results. This paper is divided into four sections. Section one describes introduction of anemia and apriori algorithm. Section two deals with literature review. Section three describes the prediction algorithm and results, and lastly, section four discusses the conclusion. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electronic health record

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An Effort Toward Localization and Recognition of Elevation Values in a Topographic Sheet 7th

An Effort Toward Localization and Recognition of Elevation V...

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7th International Conference on Communication, Device and Networking, ICCDN 2024

作者： Pradhan, Ashis Supriya, Sneha Pradhan, Mohan P. Pradhan, Ratika Department of Computer Science and Engineering Sikkim Manipal Institute of Technology Sikkim Manipal University Gangtok India Department of Computer Applications Sikkim University Sikkim India

ISBN: (纸本)9789819764648

This study focuses on efficient elevation value localization and recognition in topographic sheets (TS) through morphological operations and YOLO-based deep learning. The aim is to enhance the digitization process, crucial for creating Digital Elevation Models (DEMs) widely used in various applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Miocene

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An AI-Driven Intelligent Traffic Management Model for 6G Cloud Radio Access Networks

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IEEE Wireless Communications Letters 2023年第6期12卷 1056-1060页

作者： Swain, Smruti Rekha Saxena, Deepika Kumar, Jatinder Singh, Ashutosh Kumar Lee, Chung-Nan National Institute of Technology Department of Computer Applications Kurukshetra136119 India Goethe University Frankfurt Department of Computer Science Frankfurt60323 Germany National Sun Yat-sen University Department of Computer Science and Engineering Kaohsiung804 Taiwan

This letter proposes a novel Cloud Radio Access Network (C-RAN) traffic analysis and management model that estimates probable RAN traffic congestion and mitigate its effect by adopting a suitable handling mechanism. A computation approach is introduced to classify heterogeneous RAN traffic into distinct traffic states based on bandwidth consumption and execution time of various job requests. Further, a cloud-based traffic management is employed to schedule and allocate resources among user job requests according to the associated traffic states to minimize latency and maximize bandwidth utilization. The experimental evaluation and comparison of the proposed model with state-of-the-art methods reveal that it is effective in minimizing the worse effect of traffic congestion and improves bandwidth utilization and reduces job execution latency up to 17.07% and 18%, respectively. © 2012 IEEE.

关键词： Bandwidth

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Stock Price Prediction using Modified BPSO for Feature Selection with RNN Variants on Top Tech Companies

Stock Price Prediction using Modified BPSO for Feature Selec...

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2023 IEEE World Conference on Communication and Computing, WCONF 2023

作者： Gupta, Priyank Paharia, Nitin Gupta, Sanjay Kumar Jadon, Rakesh Singh Jiwaji University SOS Computer Science and Applications Gwalior India Prestige Institute of Management and Research Department of Computer Applications Gwalior India MITS Department of Computer Science and Engineering Gwalior India

ISBN: (纸本)9798350311204

The most often utilized data in recent years is time series data, used for things like stock market price prediction and others. Recent research has focused chiefly on stock market prediction using neural networks, and new techniques are being developed to improve these models' accuracy. One such method uses optimization algorithms like PSO, GWO, or GA. Other variants, such as Binary-PSO and Binary-GWO, are developed by further enhancing the original algorithms. The paper suggested a variant of BPSO called MBPSO / TBPSO that assigned binary values to the features during optimization using the 'tanh' activation function. The TBPSO is then applied individually for two, five, and ten years to the datasets of five leading Tech firms. The dataset, which comprises a variety of historical and technical indicators, is applied to different variants of RNN and finds the best results with the GRU model to forecast the closing stock price. What transpired proves that, when used for prediction on the GRU model and when choosing more features than BPSO, TBPSO provides us with features that will provide more accuracy. © 2023 IEEE.

关键词： Forecasting

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Flood Risk Assessment and Interpretation Using Explainable AI 2

Flood Risk Assessment and Interpretation Using Explainable A...

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Sharma, Swati Tomar, Vivek Arora, Sangeeta Gupta, Nishant KIET Group of Institutions Delhi - NCR Computer Science & Engineering Department Ghaziabad India University Computer Science & Engineering Department Dehradun India KIET Group of Institutions Delhi-NCR Computer Applications Department Ghaziabad India SET Department of Computer Science & Engineering Sharda University Greater Noida India

ISBN: (纸本)9798350368109

Floods are the unforeseen situations to the society which causes high risk to the society. For proactive action, it is important to identify locations based on past results. It is necessary to take measures before the situation gets worst. For the benefit of society, a novel approach to map flood risk usinga balanced dataset and an Extra Tree Classifier. The Extra Tree Classifier performs better with the Shapely Additive explanation values. It shows improvement towards decision making processes to reduce the causality at the time of floods. The proposed method achieves the accuracy of 93.61% for the estimating flood danger effects on a particular location. In this paper quantitative study was done to handle the challenges to predict the flood danger using the artificial intelligence ethically. © 2024 IEEE.

关键词： Risk assessment

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RECRIoT-MAC: A Reliable and Energy Efficient Resource Management for Internet of Things Based Cognitive Radio Multi- Channel MAC Protocol

RECRIoT-MAC: A Reliable and Energy Efficient Resource Manage...

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2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

作者： Agrawal, Navin Kumar Kumar, Sandeep Bisht, Girish Singh Srivastav, Akanksha Bansla, Vandna Jain, Arpit Gla University Department Of Computer Engineering And Applications U.P. Mathura India Tula's Institute Department Of Computer Science And Engineering Uttarakhand Dehradun India Shivalik Engineering College Department Of Computer Science And Engineering Uttarakhand Dehradun India Koneru Lakshmaiah Education Foundation Department Of Computer Science And Engineering AP Vaddeswaram India

ISBN: (纸本)9798350366846

Currently, the overcrowding of unlicensed spectrum bands is causing severe interference to IoT devices embedded with sensors. CR-IoT networks apply cognitive radio capabilities to the internet of things to solve the spectrum scarcity issue in conventional IoT networks. An CR radio detects available spectrum channels by dynamically modifying its programming and configuration. IoT, smart cities, and 5G all benefit from cognitive radio applications. A cognitive radio application is useful for IoT, smart cities, and 5G. Compared to benchmark Cognitive Radio MAC (CR- MAC) protocols, the proposed protocol is more reliable, intelligent, and smart. CR technology for IoT applications can be advanced by us in order to make IoT more affordable and applicable. It is demonstrated by comparing the proposed RECRIoT-MAC protocol with benchmark CR-MAC protocols that is more energy efficient and consumes less communication time. This paper examines RECRIoT-MAC's energy consumption and throughput. © 2024 IEEE.

关键词： Cognitive radio

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Blockchain - A Deployment Mechanism for IoT Based Security 1

Blockchain - A Deployment Mechanism for IoT Based Security

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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Kant, Ravi Sharma, Shashank Vikas, Vikas Chaudhary, Sachin Jain, Animesh Kumar Sharma, Kewal Krishan Iimt Engineering College Computer Science and Engineering Department Meerut India Iimt University School of Computer Science & Applications Meerut India

ISBN: (纸本)9798350338027

Implementation of IoT domain invites tremendous attacking opportunities which demands end to - end security mechanism. applications related to the domain of IoT varies from critical applications to normal business-oriented applications like Intelligent Transportation Systems, Smart Grid, Video Surveillance, Banking, Logistics, Insurance etc. A special support in terms of security must be required for critical applications as well as normal business applications. Large amount of security mechanisms implemented time to time. Blockchain technology proves to be useful in providing security to several applications based on IoT by following defense - in - depth or castle approach. Blockchain can be defined as a database for storing processed data in a sequential manner. Such data has been shared among participating users. Information can be stored on a public ledger which can't be updated. Every device in the corresponding network must retain the same ledger. Through the medium of this paper, we try to highlight importance of Blockchain Mechanism in IoT environment and also point out that the concept of Blockchain mechanism is only concerned with security. © 2023 IEEE.

关键词： Blockchain

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Development of a Novel Quality of Service Aware Video Streaming on Demand System for the Internet of Thing Enabled MANET

Development of a Novel Quality of Service Aware Video Stream...

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2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

ISBN: (纸本)9798350366846

A mobile ad hoc network (MANET) uses mobile devices and wireless networking to stream video. Several methods have been developed to address the challenges associated with video streaming over MANETs. This paper designed a new protocol for Mobile Video of Demand (MVOD) system architecture over the MANET environment. The proposed MVOD Model is used to improve the QoS parameters of the video system in wireless ad-hoc networks. The MVOD protocol uses client caching algorithms and a staggered broadcasting method, and it compares its performance with that of an existing traditional protocol for three-tier architecture. When compared to QoS parameters such as service delay and bandwidth utilization, the proposed MVOD model performs better than the traditional approach when compared with various scenarios. Based on the importance and complexity of evaluating the techniques, we conclude that comparability problems exist in research. © 2024 IEEE.

关键词： Quality of service

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Patterns of Widespread Structural Abnormalities in Autism Spectrum Disorder using Diffusion Tensor Imaging

Patterns of Widespread Structural Abnormalities in Autism Sp...

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2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

作者： Bharti, Dilip Kumar Singh, Sanjay Kumar Kumar, Mukesh Kanaujia, Vishal Kumar Aeri, Manisha Abes Engineering College Computer Science And Engineering-Data Science Ghaziabad India Kashi Institute Of Technology Department Of Computer Science & Applications Mirzamurad U.P Varanasi India Graphic Era Hill University Computer Science And Engineering Uttarakhand Dehradun248002 India Abes Engineering College Computer Science And Engineering Data Science Department Ghaziabad India

ISBN: (纸本)9798350366846

Diffusion tensor imaging (DTI) is a neuroimaging approach that lets in for the visualization and quantification of the structural integrity of white depend fibers in the brain. In latest years, DTI has come to be an essential tool for investigating the underlying neurobiological mechanisms of autism spectrum sickness (ASD), a neurodevelopmental disorder characterized via problems in social communication and repetitive behaviors. Through the usage of DTI, researchers have identified good sized styles of structural abnormalities in the brains of individuals with ASD. these abnormalities encompass changes in the microstructure of white remember fibers, along with decreased fiber density, changes in fiber directionality, and decreased connectivity between mind areas. Additionally, there may be evidence of bizarre mind development in early formative years, with a few research finding that these structural variations are present even in very younger children with ASD. One constant finding in DTI studies of ASD is reduced white rely integrity inside the corpus callosum, a large fiber package deal that connects the two hemispheres of the mind. This abnormality has been connected to deficits in social communiqué and language in people with ASD, as well as difficulties in integrating records from distinctive brain areas. The results showed extensive structural abnormalities in people with ASD in comparison to TD individuals. © 2024 IEEE.

关键词： Diffusion tensor imaging

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Mitigating Cyberbullying in Social Media: A Deep Contextual Learning Approach for Severity Level Classification in Textual Data 5

Mitigating Cyberbullying in Social Media: A Deep Contextual ...

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Agrawal, Prashant Kumar, Awanit Tripathi, Arun Kr. Sangam University Computer Science & Engineering Rajasthan India Sangam University Bhilwara Computer Science & Engineering Rajasthan India Kiet Group of Institution Department of Computer Applications Delhi-NCR Ghaziabad India

ISBN: (纸本)9798350379945

This research introduces a novel approach that integrates Deep Contextual Learning (DCL), specifically the DCL-256-32 model with an embedding model to accurately classify offense levels within the textual data. The DCL-256-32 model employs a SoftMax function to assign probabilities to distinct severity classes, ranging from critical to negligible. The proposed model incorporates two endpoints: an embedding model for generating semantic representations of input text and a set of pre-trained DCL-256-32 models for predicting offense levels. By averaging these predictions and associating them with humanreadable labels, this study proposes a robust and scalable framework for real-time text analysis. The proposed model demonstrates high performance compared to existing methods, contributing to the advancement of Natural Language Processing (NLP) and classification. This research study offers a practical solution for enhancing digital safety and combating online harassment. © 2024 IEEE.

关键词： Contrastive Learning

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