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检索条件"任意字段=International Conference on Engineering of Reconfigurable Systems and Algorithms"

共 89770 条记录，以下是391-400 订阅

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A Novel Key Generation Algorithm Utilizing Lattice-Based Cryptography Principles 3rd

A Novel Key Generation Algorithm Utilizing Lattice-Based Cry...

引用

3rd international conference on Computing and Communication Networks, ICCCN 2023

作者： Arul, Rajakumar Sivaselvam, B. Choudhary, Ankush Centre for Smart Grid Technologies Vellore Institute of Technology Chennai India Department of Computer Science and Engineering IIITDM Kancheepuram Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9789819726707

Technology advancement is inevitable, and it has created a revolution in all the sectors creating huge opportunities. Artificial intelligence and machine learning have boosted the advancement of all the sectors making the life easier and comfortable. On the other hand, these advancements highly depend on the connectivity through which all the terminals are communicating. Thus, all the technology developments depend on the communication paradigm, particularly on the wireless medium. Securing the information and infrastructure is crucial, and it demands highly complex problems that cannot be breached with high computation machines like quantum computer. The emergence of quantum computer has made all the existing cryptographic algorithms vulnerable creating a space for advanced algorithms that are safe from quantum computer attacks. Key generation is the foundational process of any cryptographic algorithm, and in this research, we propose a novel key generation mechanism based on lattice using mathematical functions. The proposal is evaluated using theoretical assumptions, and it is found to be safe and secure. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Encryption algorithms

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AI-Driven Personalized Skincare Recommendations 3

AI-Driven Personalized Skincare Recommendations

引用

3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Perumal, Iyyanar Kalaivani, P. Naveenkumar, A. Saran, V. Sriram, K. Suruthi, N. Sona College of Technology Department of Information Technology Salem India Kongu Engineering College Department of Cse Perundurai India

ISBN: (纸本)9798331509675

This study investigates the utilization of artificial intelligence (AI) to transform skincare product recommendations and the formulation of individualized routines through the analysis of user inputs and characteristics. The system utilizes data including skin type, acne count, oiliness level, and UV exposure, using KNearest Neighbors (KNN) for personalized product suggestions. Natural Language Processing (NLP) approaches are utilized to develop tailored 7-day skincare regimen recommendations by examining product and user problems, converting unstructured data into actionable insights. Moreover, deep learning algorithms are employed for real-time image-based assessments of skin conditions, facilitating precise acne diagnosis and oiliness evaluation. The system integrates visual data with textual analysis, continually adapting through user feedback to improve accuracy and relevance. This article highlights the capacity of AI-driven methods to automate routine generation and provide tailored product recommendations, fostering innovation in the cosmetics sector through a thorough, data-oriented strategy. © 2025 IEEE.

关键词： k-nearest neighbors

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A Robust and Highly Accurate Super-Resolution Time Delay Estimation Method in the Underwater Acoustic Channel 24

A Robust and Highly Accurate Super-Resolution Time Delay Est...

引用

18th ACM international conference on Underwater Networks and systems, WUWNET 2024

作者： Wu, Jie Deng, Jinhao Cui, Hongyu Zhang, Ke Harbin Engineering University China

ISBN: (纸本)9798400711602

In the underwater acoustic (UWA) channel, the time-delay estimation is a critical issue in the underwater acoustic measurements, localization, detection, and so on. However, the available bandwidth of UWA signals is narrow, the delay estimation accuracy of conventional matched filtering method is limited. Many existing time-delay super-resolution estimation algorithms perform poorly due to high computational complexity and poor robustness. In this paper, a modified Hybrid-WRELAX method is proposed to deal with the above problem. By changing the initialization parameters and the convergence conditions of the cost function, the computational complexity of the algorithm is reduced, and using the multi-parameter data fusion method to improve the robustness in the actual experimental data processing. Numerical simulations show that the modified method can resolve multipath time delay less than 0.3 times the Rayleigh limit, and the delay estimation accuracy is close to the maximum likelihood estimation in the AWGN environment. Finally, the experimental data analysis is presented to demonstrate the usability of the proposed algorithm. © 2024 Copyright held by the owner/author(s).

关键词： Delay estimation

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An Enhanced Optical-Flow Based Attendance Tracking System for Campus Environment 4

An Enhanced Optical-Flow Based Attendance Tracking System fo...

引用

4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Ram, S Karthik Somasundaram, K. Tangavel, Senthil Kumar Venkatesa, M.G. Kolandapalayam, Selvanayaki Reddy, N Manjunadh Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Coimbatore India Amrita School of Physical Sciences Department of Mathematics Amrita Vishwa Vidyapeetham Coimbatore India Ashland University Shanmugam Department of Mathematics and Computer Science United States

ISBN: (纸本)9798331523923

Manual attendance marking consumes significant time during classes, as it involves calling out students' names individually and recording their presence either physically or digitally. Although efforts to automate this process have been made, such as using biometric data like fingerprints, these methods are still time-consuming due to the need for students to queue up for scanning. A computer vision-based attendance system offers a more efficient and seamless alternative by leveraging advanced face recognition algorithms to identify students or employees automatically. This approach uses convolutional neural networks (CNNs) to extract facial features from images and match them with pre-registered data. A pipeline combining the Multi-task Cascaded Convolutional Networks (MTCNN) for face detection and alignment with the FaceNet model for recognition and classification is employed to ensure high accuracy. The system marks attendance in the backend, eliminating the need for manual intervention. Additionally, the model's performance is compared with traditional recognition and classification algorithms to demonstrate its superior efficiency and reliability, making it an ideal solution for automating attendance systems. © 2025 IEEE.

关键词： Convolutional neural networks

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Parallel Decoding of Trellis Stages for Low Latency Decoding of Tail-Biting Convolutional Codes 14

Parallel Decoding of Trellis Stages for Low Latency Decoding...

引用

14th international ITG conference on systems, Communications and Coding, SCC 2025

作者： Antonini, Amaael Sui, Wenhui Qu, Zihan Wesel, Richard D. University of California Department of Electrical and Computer Engineering Los AngelesCA90095 United States

ISBN: (纸本)9798331522896

Convolutional codes are widely used in many applications. The encoders can be implemented with a simple circuit. Decoding is often accomplished by the Viterbi algorithm or the maximum a-posteriori decoder of Bahl et al. These algorithms are sequential in nature, requiring a decoding time proportional to the message length. For low latency applications this this latency might be problematic. This paper introduces a low latency decoder for tail-biting convolutional codes TBCCs that processes multiple trellis stages in parallel. The new decoder is designed for hardware with parallel processing capabilities. The overall decoding latency is proportional to the log of the message length. The new decoding architecture is modified into a list decoder, and the list decoding performance can be enhanced by exploiting linearity to expand the search space. Certain modifications to standard TBCCs are supported by the new architecture and improve frame error rate performance. © 2025 IEEE.

关键词： Decoding

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PROPOSED CONVOLUTION NEURAL NETWORK MODEL FOR FACE RECOGNITION 19th

PROPOSED CONVOLUTION NEURAL NETWORK MODEL FOR FACE RECOGNITI...

引用

19th international Middle Eastern Simulation and Modelling conference, MESM 2024

作者： Atta, Rand A. Zghair, Noor A. Fayad, Dhiaa M. Zamil, Asmaa S. Hasan, Hussein M. Biomedical Engineering Department University of Technology Iraq Computer Engineering Department University of Technology Iraq

ISBN: (纸本)9789492859341

Face recognition is a form of biometric method that relates to the automatic recognition of faces by computerized systems through observation of the face. It is a popular feature in biometrics, digital cameras, and social tagging. Face recognition has received increased research focus in recent years. In this paper, a model of the CNN algorithm for face recognition was proposed, where a study was made on the weaknesses of previous models and concluded that if the number of images used for training is small, large models cannot learn. That is why a model was built that balances datasets with large and small sizes. In this paper, two datasets was used (Avengers Faces Dataset) this dataset contains a small number of images, and (Famous People Face Recognition) this dataset contains a large number of images. The accuracy of the proposed model of CNN in classification reached 0.9795% for the small dataset and 0.9778% for the large dataset. The tests conducted on the developed facial recognition system have demonstrated that the proposed algorithms and the developed small and big datasets of facial recognition system yield satisfactory results. © 2025 EUROSIS-ETI.

关键词： Neural network models

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The Role of Artificial Intelligence in the Diagnosis of Alzheimer's Disease - A Comprehensive Review 2

The Role of Artificial Intelligence in the Diagnosis of Alzh...

引用

2nd international conference on Machine Learning and Autonomous systems, ICMLAS 2025

作者： Pimprale, Varsha S. Gadade, Haridas D. COEP Technological University Department of Computer Science and Engineering Pune India Cummins College of Engineering for Women Department of Computer Engineering Pune India

ISBN: (纸本)9798331505745

The escalating ratio of Alzheimer's disease (AD) highlights the need for new diagnostic methods and poses significant obstacles to rapid detection and treatment. This rigorous analysis explores how artificial intelligence (AI) can improve AD diagnosis using advanced computational techniques. Artificial intelligence (AI) techniques - fuzzy logic, machine learning (ML) and natural language processing (NLP), show tremendous achievements in interpreting complex biomedical issues such as genetic profiles, clinical records, neuroimaging, etc. This study demonstrates how AI-based algorithms can improve diagnostic accuracy, predict disease progression, and enable the development of personalized treatment plans by identifying biomarkers and subtle patterns that are often missed by traditional methods. This study also covers the difficulties of using AI in clinical practice, such as the unevenness of data, ethical issues, and the requirements for interdisciplinary cooperation. This document emphasizes the revolutionary potential of AI, which combines the current development and new trends to open previous treatment and better results of patients. © 2025 IEEE.

关键词： Neurodegenerative diseases

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Smart Grid Solutions for Sustainable Mining: A Cost-Effective Energy Management Framework with Optimization algorithms 6

Smart Grid Solutions for Sustainable Mining: A Cost-Effectiv...

引用

6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Parvathareddy, Sravani Yahya, Abid Amuhaya, Lilian Livutse Samikannu, Ravi Department of Electrical and Communications Systems Engineering Botswana International University of Science and Technology Palapye Botswana Department of EEE New Era Engineering College South East Botswana

ISBN: (纸本)9798331522667

This research work focuses on conceptualizing and modeling smart grid infrastructure. The project's main objective is to develop a smart grid infrastructure to improve energy management in industrial processes. Regenerate has deployed a system that uses renewable energy sources like solar photovoltaic (PV) arrays and wind turbines combined with batteries for energy storage. This research work describes a method that first creates synthetic data and then uses a polynomial function to precisely model the statistical fluctuations inherent in the output of renewable energy sources. The process is carried out using MATLAB. A simulation model created using Simulink is also applied to build a smart grid that includes dynamic load control, demand side management DSM, and various control system configurations. The simulation demonstrates that it is possible to produce electricity with minimal or no depreciation related to an increased dependency on renewable energy sources. It can also function at a higher ratio of energy output produced by traditional sources than previously credited within New Zealand while having substantially fewer overall expenses associated with carbon emissions. © 2025 IEEE.

关键词： Demand side management

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Network and Security Solution using Jaya Algorithm-based graph search for Drone Transportation 14

Network and Security Solution using Jaya Algorithm-based gra...

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14th IEEE international conference on Communication systems and Network Technologies, CSNT 2025

作者： Patel, Pramod Kumar Khan, Nikhat Raza Mishra, Aishwarya Agrawal, Akrati Daravai, Archana Department of Electronics and Communication Engineering IES College of Technology Bhopal India Department of Computer Science and Engineering IES College of Technology Bhopal India

ISBN: (纸本)9798331531935

This study reports the suitability of several algorithms to identify the best course in a network of lines that is utilized to guide an Unmanned Arial Vehicle (UAV) aircraft in a safety configuration. It utilizes a waypoint graph using Jaya algorithm for this purpose, which is based on the GPS coordinates of flight route movement locations in three dimensions. It performs a comparative analysis of the drone path prediction using a dynamic adjacency matrix that represents the shortest path in the graph. In the context of the area observation mode, evaluate the benefits and drawbacks of the two routing methods. © 2025 IEEE.

关键词： Target drones

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Innovations in Prostate Cancer Gleason Grading: A Comprehensive Review 4

Innovations in Prostate Cancer Gleason Grading: A Comprehens...

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4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Sojitra, Harsh Patel, Pratik Piet Parul University Computer Engineering Department Gujarat Vadodara India Piet Parul University Computer Science & Engineering Department Gujarat Vadodara India

ISBN: (纸本)9798331523923

Prostate cancer is one of the most common cancers affecting men globally, and grading is crucial in treatment and survival. Structured images such as histological images that are used to determine the aggressiveness of prostate cancer and the Gleason grading system have been enhanced by ML and DL technology. However, some challenges remain though, including how to address the complexity of the histological data, how to make sure that different numbers of datasets yield similar results and how to interpret and repeat algorithms for histology. In recent years, other approaches such as transfer learning, attention mechanism, and ensemble methods seem to work relatively better but are attained with challenges like overfitting and high computational complexity. Herein the methods applied in Gleason grading classification such as datasets, ML and DL techniques and the performance measures like recall, accuracy, precision and f1-score are outlined in this review. Thus, the study provides directions for future research, the contribution and usefulness of current methods, and goals for enhancing automated Gleason grading systems. © 2025 IEEE.

关键词： Transfer learning

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