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检索条件"任意字段=IEEE Conference on Control Technology and Applications"

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Time Frame Analysis for Sentiment Prediction of Stock Based on Financial News using Natural Language Processing

Time Frame Analysis for Sentiment Prediction of Stock Based ...

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2023 International conference on Artificial Intelligence and applications, ICAIA 2023 and Alliance technology conference, ATCON-1 2023

作者： Almeida, Joy Shah, Kushal Sawant, Rupali Singh, Pratima Sardar Patel Institute of Technology Department of Information Technology Mumbai India

ISBN: (纸本)9781665456272

This research is a study on the impact of a specific stock sentiment based on its news, previous stock movements and finally finding investors sentiment over the stock. This study leverages daily Indian financial news between 2017 and 2021, extracted from various Indian and foreign news sources such as Economic Times, Money control, Livemint, Business Today, NY Times, WSJ and Washington Post. In this work we propose to analyze news data with a unique pre-processing method that uses vectorization and BERT data processing technology. This is followed by a comparative study and predictive machine learning analysis of following models - Naive Bayes and Recurrent Neural Networks (RNN) with Gated Recurrent Units (GRU), Bi-directional Long Short Term Memory (LSTM) and RNN-LSTM with the pre-processed news data leading us to better accuracy and sentiment findings as compared to other approaches. Based on the comparisons, the results show that - Bi-Directional LSTM layer based on RNN architecture along with BERT Data Processing gives an accuracy of 90.15% leading us to a conclusion of adding a layer of BERT data processing for sentiment analysis to get better results. Further an application feature is being proposed which analyzes real-time stock financial news using RNN-Bi-Directional LSTM, giving a confidence value that is used to calculate overall sentiment of a stock being traded in Indian Stock Exchange for different time frames. © 2023 ieee.

关键词： Sentiment analysis

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Model-Driven Approach for Generating Smart Contracts for Access control 5

Model-Driven Approach for Generating Smart Contracts for Acc...

引用

5th International conference on Blockchain Computing and applications, BCCA 2023

作者： Al-Azzoni, Issam Iqbal, Saqib College of Engineering Al Ain University Al Ain United Arab Emirates

ISBN: (纸本)9798350339239

Access controls are principles and policies that are deployed on a system to ensure privileged access to system resources. Role-based access controls are a type of access controls which ensure access to resources based on users' roles. There has been a recent interest in generating smart contracts for the design of access controls. Smart contracts are computerized applications or protocols which execute automatically between contributory entities without an intermediary interference. The smart contracts, however, have a limitation of being dependent on the blockchain platform for which they are designed. This limitation has been resolved by iContractML framework, which offers a provision of designing and implementing smart contracts for multiple platforms. In this study, we have used a model-driven engineering (MDE) based approach to exploit iContractML for generating smart contract for role-based access controls. We have extended the meta-model of iContractML with new notations and have used the revised meta-model to generate smart contracts for role-based access controls. The generated contracts have been thoroughly tested and evaluated for correctness. © 2023 ieee.

关键词： Smart contract

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technology Innovation and Evolution in Circuit Protection 68

Technology Innovation and Evolution in Circuit Protection

引用

68th ieee Holm conference on Electrical Contacts (HOLM)

作者： Zhou, Xin Eaton Protect Control & Solut Business 1000 Cherrington Pkwy Moon Township PA 15108 USA

ISBN: (纸本)9798350342468

Significant improvement in performance has been made over the past decades for circuit breakers due to advancement of arcing contact science, material science, and electronic technology. Two key R&D areas are interruption capability and digitization. Physical phenomena and design parameters that affect arc interruption includes arc chamber material outgassing, contact materials and post-arc current phenomena. If not properly designed, they often lead to re-ignition after current zero, resulting in failed short circuit interruption. Understanding of these phenomena and their impact on arc interruption is critical for circuit breaker development and design. More recently, driven by energy transition and future power grid needs, significant investigation and study has been made in solid state and hybrid circuit breaker technology for DC applications. This type of circuit breakers can interrupt a short circuit event within tens or hundreds of microseconds instead of milliseconds or tens of milliseconds by electromechanical circuit breakers. They enable circuit protection with bi-directional current flow, remote controllability, and software-defined functionality. This paper will highlight some of the technology development work on circuit breaker by the author and his colleagues over three decades. Meanwhile it will provide an overview of needs and emerging technologies for future circuit protection.

关键词： Arc Interruption Re-ignition Outgassing Material Contact Temperature Circuit Breaker Hybrid Circuit Breaker

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Parameter Estimation and Vector control of Induction Motor using Sciamble Workbench 7

Parameter Estimation and Vector Control of Induction Motor u...

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7th ieee International conference for Convergence in technology, I2CT 2022

作者： Harakuni, Bhagyashree Divatar, Basavarajeshwari Gurram, Nandini Sheth, Suvarna Khaded, Rakesh Pattar, Naveen Kle Technological University Department of Electrical and Electronics Engineering Karnataka India

ISBN: (纸本)9781665421683

Vector control of induction motor (IM) is widely employed in a variety of variable-speed applications drives. In order to use it, the motor parameters must be determined, and the saturation of the machine affects the motor parameters. To achieve good drive performance, IM parameters must be carefully estimated. This paper focuses on the implementation of Vector control of IM using Workbench Software, when it is operated with FOC strategy. To accomplish torque and flux decoupling in the motor, the rotor's flux vector is locked to dq coordinates, which serve as a reference frame. Workbench Software is a Model and Coding based design platform, which is used for both simulation as well as real time estimation. Simulation results are presented for different reference speeds and variation of load. © 2022 ieee.

关键词： Vector control (Electric machinery)

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Proxy-based Verification of Smart Contracts for Healthcare Domain in Blockchain Environment 4

Proxy-based Verification of Smart Contracts for Healthcare D...

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4th ieee International conference on Computing, Communication, and Intelligent Systems, ICCCIS 2023

作者： Gohil, Keyaba Gohil, Aditya Gupta, Rajesh Jadav, Nilesh Kumar Tanwar, Sudeep Nirma University Dept. of Computer Sci. and Engg. Inst. of Technology Ahmedabad382481 India

ISBN: (纸本)9798350306118

In various privacy-preserving applications, for instance, healthcare, military operations, and control systems data security and integrity are primary concerns. Malicious users attempt to modify the existing original data to falsify data jeopardizing the application. A viable solution is to utilize blockchain technology that offers essential benefits, such as immutability, transparency, trust, decentralization, and robust security. However, certain loopholes of blockchain, especially in smart contracts, make it possible for an attacker to manoeuvre critical application data. Encouraged by the aforesaid facts, we proposed a blockchain-based framework where a proxy smart contract validates the legitimacy of the smart contract used for healthcare applications. For a given public-blockchain network, many entities are willing to deploy their smart contracts. To filter out malevolent users, w e u sed a proxy smart contract as an additional security layer. It verifies all smart contracts before deploying them on the blockchain, ensuring the entry of only valid and authentic data in the blockchain. The proxy layer also eliminates the immutablity issue of smart contracts and facilitates the deployment of a new smart contract as and when required. For that, we used Remix development environment and Solidity for implementing the proxy smart contract. The potential of the proposed framework is shown by considering the blockchain's transaction and execution costs. © 2023 ieee.

关键词： Smart contract

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Common Mode Voltage Reduction Algorithm of Triple Three-Phase Motors Based on Phase Shift 6

Common Mode Voltage Reduction Algorithm of Triple Three-Phas...

引用

6th ieee International Electrical and Energy conference, CIEEC 2023

作者： Ma, Yafei Jiang, Dong Liu, Zicheng Liu, Hui Tian, Jie Li, Peng School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China School of Electrical and Electronic Engineering Wuhan Second Ship Design and Research Institute Wuhan China

ISBN: (纸本)9798350346671

Multi-phase motors have been widely studied and applied in low-voltage and high-power applications. However, under pulse width modulation (PWM), the system inevitably generates common-mode voltage (CMV), which will harm the system. In particular, the odd set of three-phase motors cannot eliminate the CMV because of its odd bridge arms. In this paper, a common-mode voltage reduction (CMVR) algorithm based on triple three-phase motors (TTPM) is proposed. Through proper zero-sequence voltage injection and pulse phase shifting, the amplitude reduction and constant amplitude control of CMV can be achieved under different maximum modulation ratios. The algorithm can effectively reduce the common mode (CM) electromagnetic interference (EMI) of the system, and the algorithm can be easily realized by carrier-based pulse width modulation (CBPWM). Finally, the simulation results show that the proposed algorithm is effective for reducing the common mode voltage of triple three-phase motors. © 2023 ieee.

关键词： Pulse width modulation

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A Novel IoT-Enabled Oxygen Delivery System with Neural Network-Based Predictive control 4

A Novel IoT-Enabled Oxygen Delivery System with Neural Netwo...

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4th International conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Sivalingam, Vijai Jayaraj, Jayakumar Paul, Subha Hency Jose Yadav, Geetika Rajasekaran, K. Raj, P. Anantha Christu Karunya Institute of Technology and Sciences Division of Biomedical Engineering Coimbatore India Karunya Institute of Technology and Sciences Division of Electrical and Electronics Engineering Coimbatore India Indian Council for Medical Research New Delhi India Kpr Institute of Engineering and Technology Department of Biomedical Engineering Coimbatore India Karunya Institute of Technology and Sciences Division of Robotics Engineering Coimbatore India

ISBN: (纸本)9798331529635

In this research study, a hardware is designed to monitor and control oxygen delivery based on physiological parameters, blood Oxygen saturation, and heart rate for real time applications. The development and evaluation of an intelligent portable Oxygen Concentrator system that integrates a Sensor, Motor driver controller, and ESP8266 microcontroller. The controller measures SPO2 and heart rate. Data from these sensors are processed by neural network model implemented on the ESP8266 which predicts the optimal Oxygen flow rate constrained internet of things (IoT) applications such as wireless sensor networks. Therefore, in this paper, the design steps to build a model in NodeMCU ESP8266 using an artificial neural network (ANN) are presented. controller is used in our study and NodeMCU ESP8266 is chosen because it is suitable to be used as a sensor node or sink in WSN applications. ANN with a Levenberg Marquardt algorithm is used as it can model the non - linearity with high accuracy. This intelligent system effectively manages Oxygen delivery, optimizing patient care, and has demonstrated high accuracy MSE of 0.0588 in predicting Oxygen flow requirements using a dataset of 1178 data points. For physiological metrics like SPO2, heart rate, respiration rate, and temperature, combining neural networks with data sets can help lower mistakes and increase the precision of predictions generated using these methods. © 2024 ieee.

关键词： Physiological models

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Energy-minimized Partial Computation Offloading in Cloud-assisted Vehicular Edge Computing Systems 20

Energy-minimized Partial Computation Offloading in Cloud-ass...

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20th ieee International conference on Networking, Sensing and control, ICNSC 2023

作者： Wang, Ziqi Li, Xinyang Wang, Jiayi Zhai, Jiahui Chen, Shichao Bi, Jing Beijing University of Technology Faculty of Information Technology Beijing China Chinese Academy of Sciences Institute of Automation Beijing China Beijing University of Technology Beijing Huairou Academy of Parallel Sensing Faculty of Information Technology Beijing China

ISBN: (纸本)9798350369502

Nowadays, the rapid advancement of Connected and Automated Vehicles (CAVs) has led to their integration with various capabilities, encompassing environmental sensing, decision-making, and multi-level assisted driving. However, the integration of computationally intensive applications like navigation and autonomous driving challenges CAVs due to their limited computational resources, necessitating the timely completion of computations. Vehicular Edge Computing (VEC) offers a solution by enabling CAVs to partially offload computation-intensive tasks to Roadside Units (RSUs) embedded with Roadside Edge Servers (RESs). Nonetheless, RSUs have finite computational resources. Therefore, a Cloud-assisted Vehicular Edge Computing (CVEC) architecture is introduced to address this problem. In this paper, we first formulate a typical CVEC system and then formulate a constrained optimization problem based on the aforementioned system, which considers both communication latency and energy consumption. Finally, a novel optimization algorithm called Whale optimization embedded with Simulated-Annealing and Genetic-learning (WSAG) is proposed to solve the above optimization problem. WSAG simultaneously determines the resource allocation and optimizes the energy consumption of the system. Experiment results prove that WSAG significantly achieves lower energy consumption with faster convergence speed than state-of-the-art peers. © 2023 ieee.

关键词： Computation offloading

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Research on Evaluation and Design of Safety Instrumented Systems Security 3

Research on Evaluation and Design of Safety Instrumented Sys...

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3rd ieee International conference on Electronic technology, Communication and Information, ICETCI 2023

作者： Fang, Laihua Shi, Xunxian Liu, Shuo Li, Pingxue China Academy of Safety Science and Technology Department of Industrial Safety Research Beijing China Qinghai Yellow River Upstream Hydropower Development Co. Ltd. Safety and Quality Department Qinghai China

ISBN: (纸本)9798350398410

As an important layer of protection for industrial security, Safety Instrumented Systems (SIS) are increasingly vulnerable to external threats such as network attacks, information leakage, and remote destruction. Security incidents involving SIS can result in significant losses to users and even endanger national security. To address this issue, the vulnerability and various threat factors of SIS security are analyzed, a method for calculating and determining the SIS information security level is presented, an SIS information security evaluation technique is developed, and information security defense countermeasures for different network architectures are designed. The risk of security incidents involving enterprise SIS is reduced by this technical method, providing a strong technical guarantee for safe and stable operations. © 2023 ieee.

关键词： National security

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AI-Enhanced Quality control Systems for Intelligent Industrial applications

AI-Enhanced Quality Control Systems for Intelligent Industri...

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2024 International conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Sreeja, S.P. Sreenivasulu, D. Jain, Alok Mittal, Mudit Subbiah, Ram Ziara, Sajjad New Horizon College of Engineering Bangalore India Institute of Aeronautical Engineering Dundigal Hyderabad500043 India Lovely Professional University Phagwara India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of Mechanical GRIET Bachupally Telangana Hyderabad India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq

ISBN: (纸本)9798350355338

Since AI has been used in industrial settings;significant changes have been made to quality control and maintenance. Adaptive Defect Net (ADN), We believe Reinforce Optimize (RO), Predictive AI-Maintain (PAM), and Predictive AI-Adaptive (PAM) can tackle smart industrial challenges. We tested and compared these tactics to famous ones. ADN's machine vision and deep learning make it quick at issue detection. We proved it was the most accurate technique to detect even the slightest issues via testing. This ensures our products fulfill our requirements. The RO offers a unique perspective on quality control improvement. Since it can mend itself and learn from its errors, it reduces check-taking staff and expenses. We observed that it may boost flexibility and ability. PAM predicts repair characteristics will occur much faster than in scheduled maintenance. Advance machine learning and sensor data analysis detect issues before they occur in predictive asset maintenance (PAM). This reduces expensive unexpected downtime and extends equipment life. The strategies exhibited greatly effect smart workplace adoption in many contexts. ADN, RO, and PAM combined provide incredible precision, speed, and flexibility in maintenance and quality control. These innovative concepts have the potential to significantly reduce costs, improve goods, and fundamentally alter the manufacturing process. The way industry does maintenance and quality control is going to undergo a radical transformation thanks to these AI-powered techniques. In the long run, this will make things more economical, dependable, and efficient. © 2024 ieee.

关键词： Predictive maintenance

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