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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Patel, Krisha R. Brahmbhatt, Vishva B. Dubey, Nilesh Jayswal, Hardik Devang Patel Institute of Advanced Technology and Research Department of Computer Engineering Vadodara India Devang Patel Institute of Advanced Technology and Research Department of Computer Science and Engineering Vadodara India Devang Patel Institute of Advanced Technology and Research Department of Infromation Technology Vadodara India

ISBN: (纸本)9798331505745

Augmented Reality (AR) and Virtual Reality (VR) are emerging technologies that combine digital and physical worlds to provide immersive and interactive experiences. Their use in education has been revolutionary, particularly in terms of increasing student engagement, grasp of complicated concepts, and encouraging experiential learning. AR superimposes virtual things on real-world surroundings, whereas VR immerses viewers in a completely digital environment. These tools gained traction during the COVID-19 epidemic, demonstrating their potential for remote learning and increasing student enthusiasm and information retention. While AR and VR are commonly employed in higher education, particularly in sectors such as healthcare and engineering, there are still barriers to their complete adoption, including cost, accessibility, and ethical concerns. This study explores the impactful uses of AR and VR in education, shedding light on their potential to modernize traditional teaching methods and improve student outcomes. © 2025 IEEE.

关键词： Students

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Backpropagation Shuffled Leaping Neural Network Implementation in Classification of DDoS Packet Flow Traffic in Data Mining

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SN computer science 2024年第8期5卷 1131页

作者： Umamaheswari, N. Kumutha, K. Kalaivani, M.S. Ramya, R. Tagore College of Arts and Science Tamilnadu Chennai India Department of Computer Application- PG Vels Institute of Science Technology and Advanced Studies Tamilnadu Chennai India Department of Computer science and Engineering Bannari Amman Institute of Technology Tamil Nadu Erode India

All web applications remember the ultimate goal of storage services, Distributed Denial of Service (DDoS), to achieve high security from various attacks. The client-server application reduces fees and runs the elite registration gadget, while the notable part assumes that it is manufactured using a grant application. Analysis of the traceback data is difficult in the previous system, and then it containsa common DDoS attack *** DDoS attacks involving different network layers such as (SIDDoS (SQL (Structured Query Language) injection), HTTP (HyperText Transfer Protocol) flood, TCP (Transmission Control Protocol) are recommended here as there are signs that new datasets of common datasets are not being collected in the proposed system. The DDoS attack classification consists of three main steps: preprocessing, trace out the source IP address, Backpropagation Shuffled Leaping Neural Network (BSLNN) based on maintaining the specifications’ integrity. The preprocessing is the first step based on the Gabor Filter used to remove the data’s noise and the second Adaboost Random Optimal Selection method to analyzethe packet flow’s relative frequency. The third step is the Backpropagation Shuffled Leaping Neural Network (BSLNN) classification of traceback data maintaining the specifications analysis’s integrity. The proposed system achieves good periodic study of packet flow accuracy and time complexity. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Adaboost random optimal selection Backpropagation Shuffled Leaping Neural Network (BSLNN) Gabor filter Preprocessing Trace out the source IP address

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Identify The Potential Instance of Copy Forgery Using Similar Algorithm 9

Identify The Potential Instance of Copy Forgery Using Simila...

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9th International Conference on advanced Computing and Communication Systems, ICACCS 2023

作者： Manikandan, A. Kumar, N. Thirumal, S. Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350397376

In a similar fashion one of the most popular types of digital art, counterfeit detection necessitates knowledge of picture structures and the ability to generate visual diversions for many purposes, including entertainment. The use of color is very crucial for creating city features. Previous studies have examined the interrelationships of color within homogenous metropolitan zones, looking for connections between neighboring areas and culturally comparable peoples. Color, acclaim, the dissemination of one's color, and satisfaction. When communicating with a foreign audience, it is common practice to have the message reviewed and edited to conform to the local language and cultural norms. © 2023 IEEE.

关键词： Color

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A Music Recommender System to Identify the Emotional State of a Person Using Machine Learning Algorithms 4

A Music Recommender System to Identify the Emotional State o...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Muruganantham, A. Malarvizhi, C. Divya Vahini, S. Saranya, D. Uthiramoorthy, A. Karnataka Bengaluru India Psg Institute of Advanced Studies Department of Computer Science Coimbatore India Dr.Mahalingam College of Engineering and Technology Department of Computer Applications Tamil Nadu Pollachi India Sri Eshwar College of Engineering Department of Information Technology Coimbatore India Rathinam College of Arts and Science Department of Computer Science India

ISBN: (纸本)9798331523923

In today's digital world, customized recommendation algorithms can improve user experiences in many different areas. Within the sphere of intelligent human-technology interaction, this paper specifically examines a music recommender system driven by machine learning algorithms. It figures out what mood users are in and can provide an appropriate response in real time. The system being propounded in this essay uses advanced technology in facial expression recognition. With the help of a webcam, it aims to accurately detect user emotions, including joy, sadness, and anger. Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) and Support Vector Machines (SVM) have been employed to effectively classify people's mood and recommend an appropriate song. Our extensive tests and examinations show that CNN, RNN, and SVM models are all very good at guessing users' moods - with high precision, recall, F1-score, and accuracy percentages. Furthermore, in-depth analyses like confusion matrixes illuminate how well each model serves as an emotion recognizer. This study's findings are representative of future prospects in affective computing around the globe with major implications for intelligent recommendation systems to which it's important that the models are sensitive. In conclusion, the suggested Music Recommender System is something new for taking a more personal view: We can be as deeply entertained as the web allows us to be - make tailored entertainment paths in the digital era. © 2025 IEEE.

关键词： Convolutional neural networks

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Continuous-Time Prediction of Industrial Paste Thickener System With Differential ODE-Net

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 686-698页

作者： Zhaolin Yuan Xiaorui Li Di Wu Xiaojuan Ban Nai-Qi Wu Hong-Ning Dai Hao Wang the Beijing Advanced Innovation Center for Materials Genome Engineering Institute of Artificial IntelligenceBeijing Key Laboratory of Knowledge Engineering for Materials ScienceSchool of Computer and Communication EngineeringUniversity of Science and Technology Beijing the Department of ICT and Natural Science Norwegian University of Science and Technology IEEE the Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and SystemsMacao University of Science and Technology the Department of Computing and Decision Sciences Lingnan University the Department of Computer Science Norwegian University of Science and Technology

It is crucial to predict the outputs of a thickening system,including the underflow concentration(UC)and mud pressure,for optimal control of the *** proliferation of industrial sensors and the availability of thickening-system data make this ***,the unique properties of thickening systems,such as the non-linearities,long-time delays,partially observed data,and continuous time evolution pose challenges on building data-driven predictive *** address the above challenges,we establish an integrated,deep-learning,continuous time network structure that consists of a sequential encoder,a state decoder,and a derivative module to learn the deterministic state space model from thickening *** a case study,we examine our methods with a tailing thickener manufactured by the FLSmidth installed with massive sensors and obtain extensive experimental *** results demonstrate that the proposed continuous-time model with the sequential encoder achieves better prediction performances than the existing discrete-time models and reduces the negative effects from long time delays by extracting features from historical system *** proposed method also demonstrates outstanding performances for both short and long term prediction tasks with the two proposed derivative types.

关键词： Industrial 24 paste thickener ordinary differential equation(ODE)-net recurrent neural network time series prediction

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Fish Species Classification Using Convolutional Neural Networks

Fish Species Classification Using Convolutional Neural Netwo...

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International Conference on IoT, Intelligent Computing and Security, IICS 2021

作者： Fatima, Nishat Yadav, Vrinda Department of Computer Science and Engineering Centre for Advanced Studies Uttar Pradesh Lucknow226031 India

ISBN: (纸本)9789811981357

Human curiosity has recently stretched beyond the ground to include the sky and the water. Automated fish categorization is becoming more popular as a way to accurately identify fish species and traits in a standardized, non-invasive, and cost-effective manner. Deep learning, which uses a variety of neural network techniques to model human brains, can be facilitated by an advanced system with efficient computation. The findings of a convolutional neural network (CNN) used to identify fish species across a large-scale fish dataset are presented in this paper. A cross-layer pooling approach is proposed, which avoids the requirement for a significant quantity of training data by leveraging a convolutional neural network as a generalized feature detector (MobileNetV2) and was successful in achieving an accuracy of 99.89% © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fish

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Early Detection of Pathological Myopia in Fundus Images Using Deep Learning 2nd

Early Detection of Pathological Myopia in Fundus Images Usin...

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2nd International Conference on Signal and Data Processing, ICSDP 2022

作者： Fatima, Nishat Yadav, Vrinda Department of Computer Science and Engineering Centre for Advanced Studies Uttar Pradesh Lucknow226031 India

ISBN: (纸本)9789819914098

High myopia or Pathological Myopia (PM) is a common cause of blindness worldwide, with a high prevalence in Asia. Pathological Myopia (PM) is a severe form of myopia that is accompanied by retinal degeneration and can result in irreversible visual loss. Patients will be able to delay or even prevent suffering from irreversible visual loss, if early discovery is followed by rapid treatment and active follow-up. Experts in Pathologic Myopia, on the other hand, are still only a few around the world. Myopic maculopathy, or Pathologic detection, is a difficult diagnosis for ophthalmologists and optometrists. As a result, automated detection utilizing Deep Learning can aid clinicians in identifying Pathologic Myopia in early stages using fundus images which are commonly used in basic eye care settings around the world, they are non-invasive and easy to obtain. Our dataset contains 473 myopic fundus images and 600 normal images. We proposed a new model based on the VGG-19 convolutional neural network with an adjusted densely connected classifier that is used in this study to achieve an accuracy of 99.069%. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Diagnosis

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High-Boost-Gain Split-Source Inverter With Shared-Ground and No Shoot-Through Issue

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IEEE Transactions on Industrial Informatics 2024年第3期20卷 3252-3265页

作者： Ahmed, Hafiz Furqan Moursi, Mohamed Shawky El Hosani, Khalifa Al Alzaabi, Omar Zahawi, Bashar National Sun Yat-sen University Department of Electrical Engineering Kaohsiung804201 Taiwan Khalifa University Advanced Power and Energy Center Department of Electrical Engineering and Computer Science Abu Dhabi127788 United Arab Emirates Mansoura University Faculty of Engineering Mansoura35516 Egypt

In this article, we propose an improved high-boost-gain split-source inverter (SSI) for renewable energy generation. The proposed inverter retains the features of the existing SSIs, such as single-stage boost inversion with a reduced number of passive components and elimination of the inverse modulation-duty relationship constraint of the impedance-source inverters. It also provides additional features that include higher boost inversion ability than existing SSIs to connect low-voltage renewable energy sources to the grid, no voltage-source short-circuit issue, which increases the robustness of the proposed inverter and pulsewidth modulation dead times can be relieved, and the negative input dc-terminal and ac-neutral are electrically connected in the proposed inverter, resulting in a constant common-mode voltage and elimination of leakage ground currents for grid-interfaced PV power systems. A detailed circuit operation and analysis is provided, and experiments are performed on a 400-VA prototype inverter to confirm the working of the proposed topology. © 2005-2012 IEEE.

关键词： Pulse width modulation

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Dual-logic-in-memory implementation with orthogonal polarization of van der Waals ferroelectric heterostructure

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InfoMat 2024年第2期6卷 107-117页

作者： Jingjie Niu Sumin Jeon Donggyu Kim Sungpyo Baek Hyun Ho Yoo Jie Li Ji-Sang Park Yoonmyung Lee Sungjoo Lee SKKU Advanced Institute of Nanotechnology(SAINT) Sungkyunkwan UniversitySuwonRepublic of Korea Department of Nano Science and Technology Sungkyunkwan UniversitySuwonRepublic of Korea Department of Electrical and Computer Engineering Sungkyunkwan UniversitySuwonRepublic of Korea IMEC HeverleeBelgium Department of Nano Engineering Sungkyunkwan UniversitySuwonRepublic of Korea

The rapid advancement of AI-enabled applications has resulted in an increasing need for energy-efficient computing ***-in-memory is a promising approach for processing the data stored in memory,wherein fast and efficient computations are possible owing to the parallel execution of reconfigurable logic *** this study,a dual-logic-in-memory device,which can simultaneously perform two logic operations in four states,is demonstrated using van der Waals ferroelectric field-effect transistors(vdW FeFETs).The proposed dual-logic-in-memory device,which also acts as a twobit storage device,is a single bidirectional polarization-integrated ferroelectric field-effect transistor(BPI-FeFET).It is fabricated by integrating an in-plane vdW ferroelectric semiconductor SnS and an out-of-plane vdW ferroelectric gate dielectric material—CuInP_(2)S_(6).Four reliable resistance states with excellent endurance and retention characteristics were *** two-bit storage mechanism in a BPI-FeFET was analyzed from two perspectives:carrier density and carrier injection controls,which originated from the out-of-plane polarization of the gate dielectric and in-plane polarization of the semiconductor,*** conventional multilevel FeFETs,the proposed BPIFeFET does not require additional pre-examination or erasing steps to switch from/to an intermediate polarization,enabling direct switching between the four memory *** utilize the fabricated BPI-FeFET as a dual-logic-inmemory device,two logical operations were selected(XOR and AND),and their parallel execution was *** types of logic operations could be implemented by selecting different initial states,demonstrating various types of functions required for numerous neural network *** flexibility and efficiency of the proposed dual-logic-in-memory device appear promising in the realization of next-generation low-power computing systems.

关键词： ferroelectric field-effect transistor in-plane ferroelectricity logic-in-memory out-of-plane ferroelectricity

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Highly Efficient Three-Level AC-AC Converter with Identical In-Phase and Antiphase Buck-Boost Operations

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IEEE Transactions on Power Electronics 2024年第8期39卷 9929-9942页

作者： Ahmed, Hafiz Furqan Khan, Ashraf Ali Al Zaabi, Omar Mousavi, Seyyed Mohammad Javad Babaei, Ebrahim National Sun Yat-Sen University Department of Electrical Engineering Kaohsiung804 Taiwan Memorial University of Newfoundland Department of Electrical and Computer Engineering Faculty of Engineering and Applied Science St. John'sNLA1C 5S7 Canada Khalifa University Advanced Power and Energy Center Department of Electrical Engineering and Computer Science Abu Dhabi127788 United Arab Emirates University of Tabriz Faculty of Electrical and Computer Engineering Tabriz51666 Iran Near East University Engineering Faculty Nicosia99138 Turkey

In this article, a new coupled-inductors based three-level bipolar buck-boost ac-ac converter is proposed. The proposed converter can produce highly efficient and symmetric in-phase and antiphase buck and boost modes of operation with much lower component voltage and current stresses. This reduces the operation and design complexity, and helps to achieve a high-efficiency operation. The high-frequency modulating switches of the proposed converter are implemented with coupled-inductor-based dual-buck phase leg, producing three-level input and output voltages, and providing inherent protection from voltage-source short-circuit issue during switch transitions. The other salient features of the proposed converter are no-commutation issue, no need for RC snubbers or dedicated safe-commutation algorithms, provision of high-quality and continuous input/output currents, and support for nonresistive loads. An in-depth circuit analysis of the proposed converter is provided based on the proposed switch modulation strategies. The guidelines for component design/selection are discussed, followed by the comparisons with state-of-the-art three-level ac-ac converters. Finally, practical circuit verifications are performed on a laboratory-assembled prototype. © 1986-2012 IEEE.

关键词： Buck-Boost converter

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