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A Novel Design of Smart and intelligent Soldier Supportive Wireless Robot for Military Operations 2

A Novel Design of Smart and Intelligent Soldier Supportive W...

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2nd ieee international conference on Advances in computing, Communication and Applied Informatics, ACCAI 2023

作者： Gnanaprakasam, C. Swarna, M. Geetha, R. Saranya, G. Shakthi Murugan, K.H. Panimalar Engineering College Department of Artificial Intelligence and Data Science Tamilnadu Chennai600123 India Dr. M.G.R. Educational and Research Institute University Department of Electronics and Communication Engineering Tamilnadu Chennai600095 India Srm Institute of Science and Technology Department of Computing Technologies Chennai India Sri Krishna College of Engineering and Technology Department of Electronics and Communication Engineering Kuniyamuthur Coimbatore641008 India Narayana Engineering College Department of Electronics and Communication Engineering Andhra Pradesh Gudur524101 India

ISBN: (纸本)9798350315905

There is an increasing desire for the deployment of military robots in today's politically unstable globe to help soldiers complete dangerous operations. The Military Rescue Robot is well-suited for performing hazardous duties including bomb disposal, observation of hostile territory, and search and rescue operations. The military and law enforcement are finding more and more uses for robots and their ancillary systems as these systems grow more technically advanced, dependable, and compact. Armed forces are increasingly relying on mobile robots for tasks like patrolling and defusing bombs. Many apps available online make use of the Bluetooth, Wi-Fi, and ZigBee technologies already present in these mobile phones in order to facilitate the remote management of additional gadgets. The livestream from the camera module and the data analysis of environmental composition by various sensors of the area under observation may help the military best prepare for missions. Arduino and Zigbee are advanced devices that might be used to achieve the aforementioned *** Zigbee is linked to the Arduino mega, which in turn is linked to the various sensors and the robotic arm. Zigbee technology is used for data transmission and reception. © 2023 ieee.

关键词： Military operations

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Artificial Intelligence (AI) Assisted Literature Review 3

Artificial Intelligence (AI) Assisted Literature Review

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3rd international conference on intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Hilda, Jabanjalin Jeevaa, S.V. Bhadhrinath, U. Solanki, Darshini Sr. School of Computer Science Engineering Vellore Institute of Technology Vellore India Vellore Institue of Tehnology Vellore Vellore India

ISBN: (纸本)9798331527549

This research aims to address the inefficiencies and inaccuracies in traditional literature review methodologies by integrating advanced Artificial Intelligence (AI) technologies, specifically transformer-based models. The study focuses on optimizing PDF-to-text conversion through image and character recognition, thereby minimizing resource wastage and errors associated with manual transcription. Additionally, the research employs advanced Natural Language Processing (NLP) techniques to automate the identification of critical phrases such as keywords and organizational entities, significantly reducing manual errors and improving accuracy. The methodology also includes the use of sophisticated summarization algorithms and sentiment analysis, streamlining the process of summarizing extensive literature and identifying study limitations. By leveraging state-of-the-art transformer models and industry-standard libraries, this research introduces a novel, efficient framework for literature analysis. The outcome is a comprehensive, AI-powered toolkit that enhances the speed, accuracy, and precision of literature reviews, ultimately providing researchers with a more reliable and resource-efficient approach to navigating scholarly content. © 2025 ieee.

关键词： Natural language processing systems

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Improving Healthcare data Management in HL7-based EHR systems with the Secure Infrastructure of Google Cloud Platform 2

Improving Healthcare Data Management in HL7-based EHR System...

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2nd international conference on intelligent Cyber Physical systems and Internet of Things (ICoICI)

作者： Ginavanee, A. Prasanna, S. VISTAS Sch Comp Sci Chennai Tamil Nadu India Agurchand Manmull Jain Coll Dept Comp Applicat Chennai Tamil Nadu India VISTAS Dept Comp Applicat Chennai Tamil Nadu India

ISBN: (纸本)9798331540661;9798331540678

The research investigates the implementation of a secure infrastructure on the Google Cloud Platform (GCP) to enhance healthcare data management within HL7-Based Electronic Health Record (EHR) systems. The study addresses challenges related to storing, processing, and accessing sensitive healthcare data by leveraging the advanced services and secure facilities offered by GCP. The study include evaluating the role of urban drainage flaws in triggering cascading effects on critical infrastructure, assessing the impact of blockchain-based electronic health record management systems, and discussing the data flow and security measures implemented within the GCP infrastructure. Methodologies employed include comparative analyses of processing time for user requests with and without authentication, comparison of time consumption and size for centralized versus blockchain-based Google Cloud Storage, evaluation of total throughput of Compute Engine instances, and analysis of variance in transfer time for file transfers. Results demonstrate the effectiveness of utilizing GCP services for secure, scalable, and efficient healthcare data management. Specifically, the proposed project achieves notable improvements in throughput efficiency, ensuring faster processing of user requests. It enhances efficiency in Google Cloud Storage time consumption, with blockchain-based storage requiring less time and space compared to centralized storage. The study highlights performance comparison between Proposed Google Cloud Storage and Amazon S3 Storage within the context of healthcare data management in HL7-based EHR systems using Google Cloud Platform's secure infrastructure. These findings contribute to the advancement of healthcare informatics and provide valuable insights for designing and deploying secure healthcare applications on cloud platforms, ultimately improving patient care and system performance.

关键词： Healthcare data Management EHR (Electronic Health Record) GCP (Google Cloud Platform) Secure Infrastructure Blockchain

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Federated Vehicular Tailgating Detection Utilizing Distance and Speed data Analytics for intelligent Transport System 10

Federated Vehicular Tailgating Detection Utilizing Distance ...

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10th international conference on Communication and Signal Processing, ICCSP 2024

作者： Velumail, Subbulakshmi Chaudhari, Shilpa Shashikant Sai Kiran, T.S. Department of Computer Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798350353068

Connected and Automated Vehicles (CAVs) are designed with sensors, cameras, and other computing devices to collect data to support cooperative intelligent Transportation systems (ITS). Many potential applications offered by CAVs exist for researchers and road safety stakeholders. Vehicle tailgating is one such application to analyze risky driving behavior. Reliable detection of such behavior is hard and expensive. This paper focuses on addressing the tailgating issue in CAVs using the dataset generated using Simulation of Urban Mobility (SUMO) for Indian roads. The proposed model of this study uses the Relative speed and Euclidean distance of the preceding and rear vehicle as parameters on the distributed Federated Learning (FL) framework to incorporate security for sensitive vehicular data. We verified our prediction model in the TensorFlow Federated framework, and our results show an accuracy of 96 percent. © 2024 ieee.

关键词： Vehicles

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Proceedings - 2023 ieee international conference on High Performance computing and Communications, data Science and systems, Smart City and Dependability in Sensor, Cloud and Big data systems and Application, HPCC/DSS/SmartCity/DependSys 2023

Proceedings - 2023 IEEE International Conference on High Per...

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25th ieee international conferences on High Performance computing and Communications, 9th international conference on data Science and systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in Sensor, Cloud and Big data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

ISBN: (纸本)9798350330014

The proceedings contain 156 papers. The topics discussed include: integrating machine learning and social sensing in smart city digital twin for citizen feedback;a novel fuzzy identity-based encryption with wireless PUF for IoT device authentication;RDA-Unet: a retrieval model for radar composite reflectivity factor from Himawari-8 observations;DHIFS: a dynamic and hybrid index method with low memory overhead and efficient file access;multi-agent reinforcement learning for smart city automated traffic light control;ST-ConvLSGRU: a radar echo extrapolation method based on LSTM and GRU;intelligent maintenance system for wind turbine based on deep belief federated learning;BioNet+: a comprehensive interaction model of finding therapeutics for diseases with graph deep learning;and PBE-Plan: periodic backdoor erasing plan for trustworthy federated learning.

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data acquisition and Monitoring Scheme for Satellite Network with Time-Varying Topology

Data Acquisition and Monitoring Scheme for Satellite Network...

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international conference on Satellite computing

作者： Zhang, Ying Wo, Tianyu Wang, Guangjian Ye, Tianyu Zhang, Jiwei Liu, Xinye Feng, Xiao Beihang Univ Beijing Adv Innovat Ctr Big Data & Brain Comp BDB Beijing Peoples R China China Elect Technol Taiji Grp Corp Ltd Beijing Peoples R China

ISBN: (纸本)9798350305883;9798350305890

As human beings further explore space, satellite systems have become an indispensable tool for human society. However, managing satellite networks, especially in edge cloud computing scenarios, presents unique challenges due to its time-varying nature. To address these challenges, we propose a novel data acquisition and monitoring scheme specifically designed for satellite network environments. Our scheme leverages eBPF (extended Berkeley Packet Filter) technology for real-time monitoring data collection and utilizes a spatial-temporal graph representation to capture the dynamic topology of the satellite network. The Max-Min Fair (MMF) algorithm is employed to compute efficient routing paths, while data preprocessing techniques are applied to alleviate data transmission pressure. The scheme is designed to support user-defined monitoring targets and enables active detection and monitoring of application processes based on specific requirements. To evaluate the effectiveness of our proposed scheme, we conduct a comparative analysis against the Shortest Path on the Spatial-Temporal graph (SPST) algorithm and the Energy-Aware Multipath (EAMP) algorithm. Experimental results demonstrate the superiority of the MMF algorithm, exhibiting a significant 32.6% and 21.5% improvement in data transmission volume compared to the SPST and EAMP algorithms, respectively. Moreover, the utilization of the MMF algorithm reduces the average satellite bandwidth utilization by 37.1% and 41.2% throughout the transmission cycle, surpassing the performance of the SPST and EAMP algorithms.

关键词： satellite network time-varying topology data acquisition monitoring scheme

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Breast Cancer Detection Using Neural Networks

Breast Cancer Detection Using Neural Networks

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2024 international conference on Advances in data Engineering and intelligent computing systems, ADICS 2024

作者： Preethi, J. Rahul Chiranjeevi, V. Dhanya Lakshmi, A. Hosala Devi, N.K. Rajalakshmi Engineering College Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

Cancer is the deadliest disease in the world, and it primarily strikes women. As early cancer detection can aid in the disease's treatment, it is imperative that the primary goal be the scientific discovery of a cancer cure. After analyzing 41 publications, we discovered that there are numerous techniques for detecting cancer. We demonstrated a deep learning neural network method for breast cancer diagnosis in this work using the Breast Cancer database. This study illustrates how deep technology and datasets can be used to learn about breast cancer diagnosis. There are three sections to this work. We started by gathering the dataset, dividing it into training and testing sets, applying a pre-processing technique to scale and filter the data, and making some graphs for data visualization. A training dataset was used to test the model, and it achieved an accuracy of 99.67%. We have shown that deep learning technologies can accurately diagnose breast cancer using the Wisconsin Breast dataset. The dataset comprises 30 features in total, and the database contains 569 rows. In this paper, we use eleven pre-processed features that we obtained to identify breast cancer. But first, we used several pre-processing techniques including Label Encoder, Normalizer, and Standard Scaler, to apply in the model and achieve good accuracy to enhance the model for breast cancer detection. © 2024 ieee.

关键词： data visualization

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intelligent System Design of Smart Hospital Based on Cloud computing 4

Intelligent System Design of Smart Hospital Based on Cloud C...

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4th international conference on Industrial IoT, Big data and Supply Chain, IIoTBDSC 2023

作者： Feng, Ying Guo, Tianqi Wang, Anqi Wen, Kai State Grid Information & Telecommunication Group Co. Ltd. Beijing Branch Beijing100031 China

ISBN: (纸本)9798350341690

With the rapid development of information technology in recent years, hospitals pay more and more attention to intelligence, especially the large domestic third-class hospitals have higher and higher requirements for intelligent construction, and the development of intelligent technology in medical field has become a hot spot in the development of information technology. Through the design of intelligent system, it can meet the information needs of medical business, provide technical support for patients' medical environment and meet the requirements of standardized operation and management of medical buildings. Through the comprehensive introduction of cloud computing technology, the intelligent degree of hospital infrastructure will be improved, the hospital management mode will be fundamentally changed, and the hospital management efficiency will be improved. This paper proposes an intelligent system design solution of smart hospital based on cloud computing, and expounds the overall architecture of the intelligent system solution of smart hospital and the design scheme of each intelligent subsystem. © 2023 ieee.

关键词： intelligent systems

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Predicting Unsettled Debts in Imbalanced data using Resampling Methods 11

Predicting Unsettled Debts in Imbalanced Data using Resampli...

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11th ieee international conference on intelligent computing and Information systems, ICICIS 2023

作者： Helmy, Abdelmoneim Elnaghy, Shaimaa Ramadan, Nagy Cairo University Faculty of Graduate Studies for Statistical Research Department of Information Systems and Technology Cairo Egypt

ISBN: (纸本)9798350322101

Unsettled debt is a central global problem for banks and businesses. Being able to accurately predict which loans will default would be incredibly valuable for understanding the state of the economy. Machine learning models can be used to predict debt defaults, which can help these organizations make better decisions and reduce their risk. This study contributed a unique dataset collected from Egyptian Social Insurance organization (NOSI) with a proposed approach for defaulted credit prediction using classification learning and resampling methods for solving imbalanced data, which is a common challenge in debt default and credit data analysis studies. The approach was evaluated using three tree-based classification algorithms: Decision Tree (DT), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). The Similarity Oversampling and Under-sampling Pre-processing (SOUP) resampling technique outperformed all other resampling techniques when applied with RF, achieving high micro-average precision and recall of 66.67% and 67.38%, respectively, compared to the original dataset's 50.42% and 50.39%. © 2023 ieee.

关键词： Forecasting

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A Feasibility Study of Real-Time, High-Speed, Multi-Channel Wireless data acquisition and Control System using MQTT Protocol 9

A Feasibility Study of Real-Time, High-Speed, Multi-Channel ...

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9th international conference on Smart computing and Communications, ICSCC 2023

作者： Sudhish Kumar, G. Chandini, G.S. Liquid Propulsion Systems Centre Kerala Thiruvananthapuram India College of Engineering Trivandrum Department of Electronics Kerala Thiruvananthapuram India

ISBN: (纸本)9798350314090

Many Industries motivated to achieve smart ways to monitor and acquire plant parameters and control plant actuators remotely. A wireless data acquisition and control system can be used for realizing smart automation. Different technologies are used to transmit the sensor data wirelessly to remote data acquisition system. Bluetooth and ZigBee technologies are the widely used short term wireless technology. In Bluetooth technology, data can be sent wirelessly to remote location, with limited range and data transfer rate. In Bluetooth 5.0, the distance is 50-60 meters and the data transfer speeds of upto 5-10Mbps. data transmission with ZigBee based network is also limited to its range and data transfer rate. The maximum range is approx. 70-100 meter and a maximum data transfer rate of 250Kbps. In order to overcome the limitations such as short range and lower data rate, a Wi-Fi based sensor network is proposed. i.e. the sensor data is transmitted to the internet server through Message Queuing Telemetry Transport (MQTT) protocol. To realize the system, different sensors are used and the sensor output is digitized through external Analog to Digital Converter ADS1115. I2C communication bus is used to establish communication between ADS1115 and NodeMCU. The Node-RED graphical programming tool is used to develop data acquisition and control software. This paper aims to change the inflexibility of wired system and develop a Real-time, High-speed, Multi-channel Wireless data acquisition and Control System. The proposed system is suitable for access Real-time data in anywhere in the world through MQTT server. Automatic/Manual control signal also can be generated from anywhere to actuate the load remotely. © 2023 ieee.

关键词： data transfer

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