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BiLSTM model with Attention mechanism for multi-label news text classification 4

BiLSTM model with Attention mechanism for multi-label news t...

引用

4th International Conference on Neural Networks, Information and Communication engineering, NNICE 2024

作者： Duan, Aihua Raga, Rodolfo C. National University College of Computing and Information Technologies Manila0900 Philippines Anhui University of Finance and Economics School of Management Science and Engineering Bengbu233030 China José Rizal University Department of Computer Studies and Engineering Mandaluyong City Philippines

ISBN: (纸本)9798350394375

Multi-label text classification is very important in text research. A news will have multiple classification labels, and the number of labels is uncertain, so how to accurately learn labels from text is difficult. In this paper, GloVe is used for vectorization, and BiLSTM is used to learn the context, Use the Attention mechanism to focus on important words in the sentence, and finally focal loss function is used as the loss function. The experimental results show that the accuracy of this method reaches 84,43%% and AUR rate is 95.98%, which are higher than the evaluation scores of other five models. © 2024 IEEE.

关键词： Classification (of information)

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Webcam-Guided Gesture-Controlled Robotic Arm 3

Webcam-Guided Gesture-Controlled Robotic Arm

引用

3rd IEEE World Conference on Applied Intelligence and computing, AIC 2024

作者： Singh, Kanishk Joshi, Aditya Bhatt, Jaishankar Juyal, Amit Rawat, Manmohan Singh Graphic Era Deemed to Be University Department of Computer Applications Dehradun India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Graphic Era Hill University School of Computing Dehradun India Uttarakhand State Council for Science and Technology Dehradun India

ISBN: (纸本)9798350384598

This paper focuses on the design of a gesture-controlled robotic arm that is navigated with the help of a webcam and OpenCV-enabled real-time hand tracking. Embedded with OpenCV's hand tracking module, the system successfully identifies the hand landmarks from the live camera captured hand movement of the user. By the current state of each finger, the state is represented by a string format that includes the symbol and number (such as00010) that is transmitted to an Arduino Uno board, the robotic arm can move its fingers up or down. Control of the flows of the movement of the robotic arm is done using the Arduino Uno whereby the servo motors receive signals to move 0 or 180 degrees. This is mainly due to the efficiency, precision and short latency of the suggested system which makes it novel that gives the user a simple graphics interface to control robotic arms without necessity to know programming or have specific hardware. This technology provides an effective solution in robotic manipulation and presents the enormous potential to enhance HRI in different application areas. © 2024 IEEE.

关键词： Robotic arms

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Koopman-Based Model Predictive Control of Quadrotors

Koopman-Based Model Predictive Control of Quadrotors

引用

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Simone Martini Edoardo Todde Margareta Stefanovic Matthew J. Rutherford Alessandro Rizzo Kimon P. Valavanis Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer Science University of Denver USA Department of Electronics and Telecommunications Torino Italy Department of Computer Science Ritchie School of Engineering and Computer Science University of Denver Denver USA

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

A novel formulation of model predictive control (MPC) coupled with Koopman operator theory is presented and tested for the trajectory tracking problem of a quadrotor UAV. The analytical derivation of Koopman observables allows for the quadrotor model to be written as a fully-actuated quasi-linear system which enables the control problem to be posed as a linear control problem. In fact, the adopted approach embeds the quadrotor nonlinear dynamics into a quasi-linear form through the evolution of the Koopman op-erator generalized eigenfunctions, a special kind of Koopman observables. Hence, the linear MPC formulation in Koopman coordinates is equivalent to a nonlinear implementation in the original state space. Moreover, in an enhancement from the standard feedback linearization, the Koopman based quadro-tor model does not present underactuation, which drastically simplifies the computational requirement for the solution of the MPC optimization problem. The presented methodology is tested through detailed numerical simulations and results are compared to single-loop nonlinear MPC (NMPC). The satisfactory tracking performance are additionally enhanced by the obtained computational speedup which is crucial for real time implementation of flight controllers.

关键词： Computational modeling Numerical simulation Mathematical models Eigenvalues and eigenfunctions Nonlinear dynamical systems Numerical models Feedback linearization MATLAB Quadrotors Predictive control

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Angularly Stable, Single-Layer Absorptive Metasurface for X-Band Applications 2

Angularly Stable, Single-Layer Absorptive Metasurface for X-...

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2nd International Conference on Microwave, Antennas and Circuits, ICMAC 2025

作者： Shafi, Muhammad Danial Hassan, Ahsaan Gul Ildes, Harun Ullah, Inam Shoaib, Nosherwan Nikolaou, Symeon School of Electrical Engineering and Computer Science (SEECS) National University of Sciences and Technology (NUST) Islamabad 44000 Pakistan Hacettepe University Department of Electrical and Electronics Engineering Ankara Turkey Frederick Research Center Nicosia Cyprus Frederick University Electrical Engineering Department Nicosia Cyprus

ISBN: (纸本)9798331518424

This work presents the design of a single-layer absorptive metasurface capable of achieving broadband absorption across the X -band over a wide range of incidence angles. The design introduces novelty through its unit cell configuration, angular stability, enhanced fractional bandwidth, and absorption without the use of an air gap. Both measured and simulated results are in strong agreement, underscoring the potential of the proposed metasurface for radar cross-section (RCS) reduction applications. Overall, the absorption ratio (AR) exceeds 80% for incidence angles up to 50°, highlighting its effectiveness for practical applications. © 2025 IEEE.

关键词： Absorption Ratio (AR) Absorptive Metasurface (AM) Radar Cross-Section (RCS)

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Deep Learning Approach for Predicting Output Current Ripple in Electric Vehicle Chargers 7

Deep Learning Approach for Predicting Output Current Ripple ...

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Madumathi, K. Saravanan, T.S. Khandan, K. Lakshmi Raja, R. Kannan, Sathish Rajendiran, M. Mahendra Institute of Technology Department of Electrical And Electronics Engineering Namakkal Tamil Nadu Mallasamudram637503 India Rajalakshmi Engineering College Department of Electrical And Electronics Engineering Chennai Tamil Nadu Thandalam602105 India Madanapalle Institute of Technology & Science Department of Electrical And Electronics Engineering Andhra Pradesh Madanapalle517325 India Pandian Saraswathi Yadav Engineering College Department of Electronics And Communication Engineering Sivagangai Tamil Nadu Madurai630561 India Saveetha Institute of Medical And Techinical Sciences Saveetha School of Engineering Department of Vlsi Microelectronics Tamil Nadu Chennai602105 India Panimalar Engineering College Department of Computer Science And Engineering Tamil Nadu Chennai600123 India

ISBN: (纸本)9798350359299

Significant attention in the field of Electric Vehicle (EV) battery development has been directed towards enhancing the longevity of the batteries. EV batteries commonly experience severe power ripples throughout the charging and power conversion operations, which might cause battery deterioration, especially in low-temperature conditions. The term "ripple"generally refers to undesired variations in the AC voltage when applied to a DC power source. Ripple current is generated by motor drivers, power conversion elements, DC power outlets, on-board chargers, and brake charging. This research addresses the essential need for predicting ripple current to maintain the quality and longevity of EV batteries. The study used Deep Learning (DL) models, namely Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory (Bi-LSTM), to predict output current ripple in EV chargers. The EV charger circuit simulation provides a total of 336 data points, 300 of which are used for training and 36 are stored for model testing. Both models are evaluated using performance criteria throughout the testing phase. Bi-LSTM achieves a better coefficient of determination (R2), with a value of 0.9879. A range of error metrics are employed to conduct a full examination, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), and root mean squared error (RMSE). The simulation findings reveal that Bi-LSTM significantly improves the prediction accuracy of output current ripple. © 2024 IEEE.

关键词： Long short-term memory

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Efficient Optimal Control of Open Quantum Systems 19

Efficient Optimal Control of Open Quantum Systems

引用

19th Conference on the Theory of Quantum Computation, Communication and Cryptography, TQC 2024

作者： He, Wenhao Li, Tongyang Li, Xiantao Li, Zecheng Wang, Chunhao Wang, Ke Center for Computational Science and Engineering MIT CambridgeMA United States School of Physics Peking University Beijing China Center on Frontiers of Computing Studies School of Computer Science Peking University Beijing China Department of Mathematics Pennsylvania State University University ParkPA United States Department of Computer Science and Engineering Pennsylvania State University University ParkPA United States

ISBN: (纸本)9783959773287

The optimal control problem for open quantum systems can be formulated as a time-dependent Lindbladian that is parameterized by a number of time-dependent control variables. Given an observable and an initial state, the goal is to tune the control variables so that the expected value of some observable with respect to the final state is maximized. In this paper, we present algorithms for solving this optimal control problem efficiently, i.e., having a poly-logarithmic dependency on the system dimension, which is exponentially faster than best-known classical algorithms. Our algorithms are hybrid, consisting of both quantum and classical components. The quantum procedure simulates time-dependent Lindblad evolution that drives the initial state to the final state, and it also provides access to the gradients of the objective function via quantum gradient estimation. The classical procedure uses the gradient information to update the control variables. At the technical level, we provide the first (to the best of our knowledge) simulation algorithm for time-dependent Lindbladians with an 1-norm dependence. As an alternative, we also present a simulation algorithm in the interaction picture to improve the algorithm for the cases where the time-independent component of a Lindbladian dominates the time-dependent part. On the classical side, we heavily adapt the state-of-the-art classical optimization analysis to interface with the quantum part of our algorithms. Both the quantum simulation techniques and the classical optimization analyses might be of independent interest. © Wenhao He, Tongyang Li, Xiantao Li, Zecheng Li, Chunhao Wang, and Ke Wang.

关键词： Optimal control systems

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Sybil Assault Detection in VANET with Efficient Network Analysis

Sybil Assault Detection in VANET with Efficient Network Anal...

引用

MIT Art, Design and Technology school of computing International Conference (MITADTSoCiCon)

作者： Shubhra Mukherjee Mathur Nagesh Jadhav Ravindra Gupta Department of Computer Science and Engineering School of Computing MIT Art Design and Technology University Pune Sarvepalli Radakrishnan University Bhopal Department of Computer Science and Engineering School of Computing MIT Art Design and Technology University Pune Department of Computer Science and Engineering School of Computing Sarvepalli Radakrishnan University Bhopal

ISBN: (数字)9798350362879

ISBN: (纸本)9798350362886

A developing technology that can be highly helpful for both intelligent transportation services and safety and security is the Automobile ad hoc network, or VANET. Nevertheless because of the great mobility and wireless connection of cars, there are numerous security risks that jeopardize people's safety and security when driving. The Sybil assault, in which the perpetrator makes up a false identity to obtain significant influence within the network and delay certain services and manipulate others by fictitious voting, is one of the main security issues. People can avoid being duped by an attacker or falling into traps when attacks are detected early.. This study describes two methods for detecting Sybil attacks: the first uses the Poisson Distribution Method in order to forecast traffic on the street, whereas the latter examines network efficiency for packet delivery ratio (PDR) in both benign additionally malicious environments. According to the simulation's findings, PDR lowers the number of fictitious cars in the network. Our method is straightforward and efficient because it doesn't involve a lot of computational overhead and doesn't breach users' privacy concerns.

关键词： Wireless communication Privacy Vehicle detection Vehicular ad hoc networks Transportation Network analyzers Safety

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Block Chain based Secured Wireless Patient Health Monitoring System 7

Block Chain based Secured Wireless Patient Health Monitoring...

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7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Benvin, Shalet Arvind, R. Sugunadevi, C. Gomathi Meena, S. Oommen, Sujo Maranan, Ramya Bgs Institute of Technology Computer Science and Engineering Karnataka India Cmr Institute of Technology Information Science and Engineering Karnataka India Vidhya Sagar Women's College Department of Computer Science Tamil Nadu Chengalpet India Reva University School of Electrical and Electronics Engineering Bangalore India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai India

ISBN: (纸本)9798350341485

The patient health monitoring approach based on the Internet of Things (IoT) consists of smart electronic devices and protocol that communicate to the data via the internet. The medical field now has countless new avenues to explore because of this discovery. Health information and additional symptom information can be gathered by associated smart sensors. This allows the patient to reach the right healthcare specialist, thus facilitating distant care. However, there are concerns about hacking and confidentiality of medical data in IoT platforms. As a result, it is crucial to develop specific safety protocols for IoT-based patient health monitoring system. Researchers periodically propose a new strategy for protecting data collected by IoT-based healthcare devices. The data can be vulnerable to numerous forms of attacks. Thus, the researchers proposed the notion of enhancing the security of the IoT-based patient health monitoring system by incorporating blockchain technology. This research study suggests a Blockchain-based XOR Elliptic Curve Cryptography (XORECC) method for securing an IoT healthcare monitoring system against a wide range of possible attacks. The proposed method is evaluated against the traditional approaches like Advanced Encryption Standard (AES) and Rivest-Shamir-Adleman (RSA). The experimental findings confirm that the suggested approach provides a very high level of security for data transmission over the IoT. © 2023 IEEE.

关键词： Internet of things

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Lightweight Federated Learning for COVID-19, Pneumonia, and TB from Chest X-Ray Images 1

Lightweight Federated Learning for COVID-19, Pneumonia, and ...

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1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Trivedi, Naresh Kumar Maheshwari, Himani Tiwari, Raj Gaurang Agarwal, Ambuj Kumar Gautam, Vinay Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School of Computing Graphic Era Hill University Uttrakhand Dehradun India Sharda School of Engineering and Technology Sharda University Department of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350330915

The COVID-19 virus, often known as the coronavirus, poses a severe threat to international health. The vast amount of chest X-ray (CXR) images may be evaluated by radiologists with deep learning, which could significantly streamline and speed up the diagnosis of pneumonia, TB, and COVID-19. Such methods necessitate extensive training datasets, all of which must be consolidated for processing. Patient information cannot be compiled and shared on a centralized server due to medical data privacy restrictions. This paper describes a federated learning architecture that enables deep learning to be used by different hospitals to screen chest X-rays for COVID-19, Tuberculosis, and Pneumonia without sharing patient data. We investigate the naturally occurring unbalanced data distributions and the fact that they are not independent and non-identically distributed (non-IID) in a federated learning environment. This work offers a federated learning framework that is applicable to different transfer learning models like AlexNet, SqueezeNet, and ResNet architectures. Resnet50 model with a federated learning environment produces 98.73% of classification accuracy results. These results would lead medical institutions to adopt a collaborative process and use the private data rich in COVID-19 and other chest-related diseases to construct a robust model swiftly. © 2023 IEEE.

关键词： covid19 federated learning machine learning pneumonia tuberculosis

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Instantaneous Interpretation into Sign Language for the Hearing Impaired 1

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

作者： Singh, Kamred Udham Kumar, Ankit Kumar, Gaurav Singh, Teekam Kothari, Paras Sheikh, Anisha School of Computing Graphic Era Hill University Dehradun India Department of Information Technology Guru Ghasidas Vishwavidyalaya Bilaspur India Department of Computer Engineering and Applications GLA University UP Mathura India Department of Computer Science and Engineering Graphic Era Deemed to Be University Dehradun India Department of Computer Applications Geetanjali Institute of Technical Studies Rajasthan Udaipur India

ISBN: (数字)9789819738106

ISBN: (纸本)9789819738090

Because they are unable to convey their thoughts to others who can hear, deaf persons may have a difficult time controlling their emotions and may find that their routines are often interrupted. This is the primary impetus behind the progression of things. These individuals would be helped by this system, and it would make it possible for them to convey their ideas in a manner that is on par with that of persons who do not have any kind of physical impairment. Recent advances in artificial intelligence have made it possible to design a system that is capable of resolving this problem, which was previously thought to be impossible. The purpose of this research is to develop, for the benefit of the deaf community, a system that can translate speech into text. Because it’s possible that some individuals won’t comprehend only the written word, the speech will also be translated into international sign language (ISL). In this method, persons who are deaf or hard of hearing will have their sign language translated into spoken language. In order to develop the most accurate model possible, we will integrate NLP with a variety of ML and AI techniques. For the purpose of prediction, convolutional neural networks (CNN) will be used since lip movements are continuous and rapid, making them challenging to capture. CNN and attention-based long and short-term memory (LSTM) approaches will function since they are both effective at predicting visual input. In order to get more desirable results, we will be using several techniques for augmenting the data. TensorFlow and Keras are going to be the Python libraries that are employed in order to do the voice-to-text translation. At the moment, there is an abundance of software accessible;however, all of them require the use of a network. This piece of hardware can function very well without being connected to the internet. Using the suggested technique, we were able to attain a 100% accuracy rate in sign language prediction and a 96% a

关键词： Forecasting

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