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Psychological Restrain for Fault Detection in Reinforcement Learning 4

Psychological Restrain for Fault Detection in Reinforcement ...

引用

4th ieee international conference on Computing, communication, and intelligent Systems, ICCCIS 2023

作者： Phour, Himanshi Gautam, Neha Gaurav, Abhilash Chandigarh University Department of Computer Science and Engineering Punjab Gharuan India

ISBN: (纸本)9798350306118

Reinforcement learning is a sub part of machine learning that aims for adapting its agent or agents to the unfeasible environment with a solo purpose of achieving the maximum rewards. In common RL agents are trained to find the optimum policy for the varied actions and to achieve the maximum rewards possible. Markov Decision processes that call a rule of penalty if and only if it got the penalty or transit to achieve the penalty. But however, getting all the data set values that shows all those transit states or chances where it couldn't be able to get the rewards. In this paper, we put forward the Reinforcement Learning psychological restrain for fault detection that will visualize the restrains that block the agent to optimize the rewards. these bugs can be in the logical part of the code or there might be a misplaced value of rewards or penalty that got missed by the programmer. Its effectiveness can be shown via snake game. © 2023 ieee.

关键词： Fault detection

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A Comparative Analysis of Various Machine Learning Algorithms for Handwritten Digit Recognition 4

A Comparative Analysis of Various Machine Learning Algorithm...

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4th ieee international conference on Computing, communication, and intelligent Systems, ICCCIS 2023

作者： Akshat, Abhi Tripathi, Kritika Malik, Devanshi Fatima, Hoor Sharda University Department of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350306118

One of the most fundamental uses of machine learning is the identification of handwritten digits. there has been a lot of compelling research in this field. Since everyone has different handwriting, it becomes very important for the algorithm to recognize all styles and ways of writing. With the advancement in science and technology, digitization of all forms of documents has become prominent. Since there are still many documents that are yet to be digitized, these applications come in handy. MNIST and SKLearn load digits datasets are prominent for the recognition process and they have a large set of data points. Many Algorithms are developed over the years that are capable of performing recognition of digits. the accuracy and performance metrics of the methods Support Vector Machine (SVM), Random Forest, Gaussian Naive Bayes, and Convolutional Neural Networks (CNN) are analyzed in this study. © 2023 ieee.

关键词： Support vector machines

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A Comparative Study of Deep Learning Techniques for Network Intrusion Detection 4

A Comparative Study of Deep Learning Techniques for Network ...

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4th international conference on Emerging Systems and intelligent Computing, ESIC 2024

作者： Pant, Pranav Kumar, Aniket Vashishtha, Lalit Kumar Dash, Subhasis Ray, Niranjan Kumar Sahu, Santosh Kumar Kiit University School of Computer Engineering Bhubaneswar India Oil and Natural Gas Coorporation Ltd Geodata Processing and Interpretation Center Dehradun India

ISBN: (纸本)9798350349856

In an era dominated by interconnected technologies, the persistent threat of intrusion attacks looms ominously, leaving individuals and organizations vulnerable to devastating consequences. the insidious nature of these attacks not only compromises sensitive information but also jeopardizes the very fabric of digital trust. As the frequency and sophistication of intrusions escalate, there is an urgent need for robust defenses to safeguard against these malicious incursions. this paper addresses this pressing concern by delving into the realm of deep learning, a cutting-edge field that holds the promise of fortifying our digital fortresses. We present a comprehensive analysis of various deep learning approaches, rigorously tested on two benchmark datasets: UNSW-NB15 and 5G-NIDD. these datasets serve as battlegrounds where our models are trained and tested to discern their efficacy in the critical task of intrusion detection. © 2024 ieee.

关键词： Intrusion detection

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intelligent Doctor Chatbot 4

Intelligent Doctor Chatbot

引用

4th international Multidisciplinary Information Technology and Engineering conference, IMITEC 2024

作者： Khoza, Mahlori Olaifa, Moses Owolawi, Pius Malele, Vusi Tshwane University of Technology Dept. of Computer Systems Engineering Tshwane South Africa

ISBN: (纸本)9798350387988

this study proposes a cutting edge intelligent Doctor Chatbot that improves healthcare delivery and provides patients with easily accessible and customized health related information through the use of Natural language processing (NLP) and artificial intelligence (AI) technologies. these technologies are used by the chatbot to provide accurate medical advice based on symptom analysis and general health guidance in an interactive manner. the doctor chatbot addresses the growing demand for reliable healthcare information and assistance, particularly in situations where access to medical professionals is limited. By leveraging its advanced algorithms and medical knowledge base, the chatbot provides users with quick and accurate answers to their health-related questions. A key feature of the doctor chatbot is that users describe their symptoms and receive preliminary assessments on potential causes and suggested courses of action. It allows people to take an active role in their healthcare management and preventive measures. © 2024 ieee.

关键词： Diagnosis

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Comparison of Proposed Plant Leaf Diseases Detection Algorithm with Existing State-Of-the-Art Techniques 4

Comparison of Proposed Plant Leaf Diseases Detection Algorit...

引用

4th ieee international conference on Computing, communication, and intelligent Systems, ICCCIS 2023

作者： Mitra, Dipra Gupta, Shikha Computer Science and Engineering Chandigarh University Punjab India

ISBN: (纸本)9798350306118

Despite a significant increase in population, agriculture still supplies food for everyone. It is crucial to anticipate plant diseases in the agricultural sector at an early stage since doing so will ensure that there is enough food for everyone. Unfortunately, infections can be foreseen at such an early stage in the crop cycle. the paper's objective is to increase farmers' comprehension of cutting-edge methods for decreasing plant leaf disease. Since there are few vegetables other than potatoes, tomatoes, and mangoes, a precise algorithm and machine learning approaches have been designed to identify leaf diseases. this study takes into account samples of mango, tomato, and potato leaves that have anomalies. Based on the suggested algorithm, a comparison study has been conducted with the help of a confusion matrix. © 2023 ieee.

关键词： Fruits

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Advancements in Unsupervised Feature Learning for Image Data 4

Advancements in Unsupervised Feature Learning for Image Data

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4th ieee international conference on Computing, communication, and intelligent Systems, ICCCIS 2023

作者： Karki, Uttam Shakya, Subarna Institute of Engineering Tribhuvan University Department of Electronics and Computer Engineering Pulchowk Campus Kathmandu Nepal

ISBN: (纸本)9798350306118

this research addresses the challenge of unsupervised landmark learning in the presence of non-parameter data, where image pairs exhibit significant variations in appearance and posture. Traditionally, unsupervised landmark learning relies on synthetic image pairs with similar appearances but differing postures. However, these synthetic pairs, generated through predefined transformations, do not accurately represent real-world appearance and pose changes. To overcome this limitation, we propose a novel approach incorporating Cross-Picture Cycle Compatibility (C3). We iteratively apply the technique of reconstructed exchange twice to establish comprehensive supervision, with a primary focus on maintaining cycle consistency within the framework. Additionally, we introduce a cross-picture flow to ensure the consistency of image landmarks. © 2023 ieee.

关键词： Iterative methods

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Design of CAN Bus Dual Redundancy Scheme Based on FPGA 9

Design of CAN Bus Dual Redundancy Scheme Based on FPGA

引用

9th international conference on intelligent Computing and Signal processing, ICSP 2024

作者： Kang, Lei Wang, Jinjin School of Computer Science Xi'an Shiyou University Yanta Shaanxi Xi'an China

ISBN: (纸本)9798350376548

In view of the continuous expansion of the current CAN bus communication network, which brings a lot of problems such as paralysis of the communication network due to wiring failures, a dual redundancy scheme for the CAN bus based on FPGA is proposed. the aim of this paper is to make the reliability of CAN bus data transmission improved by using CAN controller redundancy technology and improving the overall integration of nodes. the system uses FPGA chip as the hardware entity carrier and integrates two self-implemented CAN controller IPs to achieve CAN bus communication. When the system is running, the two CAN channels work synchronously, and when one channel fails, it can carry out bus hot-switching in time to ensure uninterrupted operation of the system, which effectively improves the reliability of the CAN communication network. © 2024 ieee.

关键词： Integrated circuit design

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Wireless Broadband Ad Hoc Network communication Algorithm Based on IGS Technology 4

Wireless Broadband Ad Hoc Network Communication Algorithm Ba...

引用

4th ieee international conference on Mobile Networks and Wireless communications, ICMNWC 2024

作者： Wang, Haigang Ren, Liming Dai, Chen Jiang, Jiafeng School of Information Science and Technology Tsinghua University Beijing China School of College of Electronic Information and Electrical Engineering Hefei University Anhui Hefei China Nanjing University of Engineering Department of Computer Engineering Jiangsu Nanjing China School of Information Engineering Inner Mongolia University of Science and Technology Inner Mongolia Baotou China

ISBN: (纸本)9798350352931

In response to the problems faced by traditional wireless broadband ad hoc network communication algorithms in dealing with complex and changing network environments, this paper introduces the IGS (Imperfer Gaussian Signaling) technology based on wide linear new waveforms, aiming to improve the transmission efficiency and anti-interference ability of devices. Firstly, the study aims to optimize communication requirements in multiple scenarios of power business;then, the use of IGS technology is studied to convert non-circular signals into Gaussian distribution signals;finally, the study is conducted on intelligent routing algorithms based on wide linear new waveform to optimize path selection between nodes and dynamically adjust topology connections, thereby enhancing the system's self-organization capability and network throughput. As the number of nodes continues to increase to 500, the latency of traditional systems has risen to 33 milliseconds. Wireless broadband self-organizing network communication devices based on IGS technology provide efficient and stable solutions for large-scale self-organizing network applications in the power industry. © 2024 ieee.

关键词： Ad hoc networks

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Dynamic User Interface Generation for Enhanced Human-computer Interaction Using Variational Autoencoders 4

Dynamic User Interface Generation for Enhanced Human-Compute...

引用

4th international conference on communication Technology and Information Technology, ICCTIT 2024

作者： Zhang, Runsheng Wang, Shixiao Xie, Tianfang Duan, Shiyu Chen, Mengmeng University of Southern California Los AngelesCA United States School of Visual Arts New YorkNY United States Georgia Institute of Technology AtlantaGA United States Carnegie Mellon University PittsburghPA United States New York University New YorkNY United States

ISBN: (纸本)9798331528973

this study presents a novel approach for intelligent user interaction interface generation and optimization, grounded in the variational autoencoder (VAE) model. With the rapid advancement of intelligent technologies, traditional interface design methods struggle to meet the evolving demands for diversity and personalization, often lacking flexibility in real-time adjustments to enhance user experience. Human-computer Interaction (HCI) plays a critical role in addressing these challenges, as it focuses on creating interfaces that are not only functional but also intuitive and responsive to user needs. this research leverages the RICO dataset to train the VAE model, enabling the simulation and creation of user interfaces that align with user aesthetics and interaction habits. through the integration of real-time user behavior data, the system dynamically refines and optimizes the interface to improve usability, thereby underscoring the importance of HCI in achieving a seamless user experience. the experimental findings indicate that the VAE-based approach significantly enhances the quality and precision of interface generation compared to other methods, including autoencoders (AE), generative adversarial networks (GAN), conditional generative adversarial networks (cGAN), deep belief networks (DBN), and variational autoencoder generative adversarial networks (VAE-GAN). this work contributes valuable insights into Human-computer Interaction (HCI), providing robust technical solutions for automated interface generation and enhanced user experience optimization. © 2024 ieee.

关键词： Generative adversarial networks

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Automated Attendance Management System Using Face Recognition and Real-Time Biometric Authentication 4

Automated Attendance Management System Using Face Recognitio...

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4th international conference on Ubiquitous Computing and intelligent Information Systems, ICUIS 2024

作者： Ida Christy, J. Abisha, D. Mithunkumar, C. Navedha Evanjalin, R. Ajith, S. Dharun Ram, K. National Engineering College Department of Computer Science and Engineering Kovilpatti India

ISBN: (数字)9798331529635

ISBN: (纸本)9798331529635

Tracking attendance in educational institutions is an extremely time-consuming and labor-intensive process, and the task seems to be plagued by inaccuracies and inefficiencies at all times. Techniques such as manual roll calls or traditional paper-based attendance systems often face problems like proxy attendance and human error, coupled with delays due to the processing of a large volume of data. the more the number of students, especially with an increasing need to operate with fewer numbers of people, there is a growing need for more efficient, reliable, and secure attendance tracking. Also, the growing administrative and academic interests of accurate attendance records affirms that current techniques of recording attendance lack the necessary level of efficiency. Attendance management systems in the conventional sense faced problems and constraints, and this paper specifically on the pressures toward discovering a solution that can automate the process yet has validity, security, and scalability issues. © 2024 ieee.

关键词： Authentication

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