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Optics Continuum 2025年第4期4卷 789-803页

作者： Esteban Farfán-Guillén, David Camporez, Higor Silva, Jair Adriano Lima Castellano Rodriguez, Juan Camilo Pohl, Alexandre De Almeida Prado CPGEI–Graduate Program in Electrical Engineering and Computer Science Federal University of Technology Paraná Curitiba80230–901 Brazil Graduate Program in Electrical Engineering Federal University of Espírito Santo Vitória29075-960 Brazil

Visible light communications (VLC) enable wireless data transmission using existing light-emitting diode (LED) illumination. This experimental study evaluates the performance of multiple input and multiple output (MIMO) configurations in indoor VLC systems by analyzing their impact on both communication and illumination. Various MIMO setups (2 × 2, 3 × 2, and 4 × 2) are compared against single input single output (SISO), and single input multiple outputs (SIMO) schemes, using commercial LED luminaires as transmitters. While the 4 × 2 MIMO configuration demonstrates superior overall performance, intermediate configurations like 3 × 2 or 2 × 2 MIMO offer an attractive trade-off between system complexity and performance enhancement, particularly in scenarios with space or cost constraints. The results show that MIMO configurations significantly outperform SISO systems, achieving reliable communication (BER ≤ 10−3) at practical indoor distances of up to 2 meters while maintaining illumination levels above 300 lux, where conventional SISO setups do not meet these dual requirements. These findings demonstrate the practical feasibility of MIMO-VLC systems for indoor deployments. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Frequency division multiplexing Modulation techniques Multiple input multiple output Quadrature amplitude modulation Signal processing Visible light communications

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FPGA implementation of low cost and low power chaotic encryption scheme based on a discrete-space chaotic map

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Multimedia Tools and Applications 2025年 1-22页

作者： Moreira Bezerra, João Inácio Machado, Gustavo Iankowski Soares, Rafael Valduga de Almeida Camargo, Vinícius Molter, Alexandre Post Graduate Program in Computer Science Universidade Federal de Pelotas Rio Grande do Sul Pelotas96010610 Brazil Graduate Program in Computer Engineering Universidade Federal de Pelotas Rio Grande do Sul Pelotas96010610 Brazil Post Graduate Program in Mathematical Modeling Universidade Federal de Pelotas Rio Grande do Sul Capão do Leão96160000 Brazil

The exponential growth of the number of devices connected to the Internet and the use of IoT applications increases the amount of data exchange over public channels in low-cost and low-power embedded systems. Images are the most widely shared files, and standard symmetric algorithms such as the Advanced Encryption Standard (AES) are optimized for text but not image encryption. Consequently, new approaches like chaotic encryption have attracted researchers’ interest. Chaotic encryption schemes have been analyzed mostly from a software standpoint, but recent advancements in the field, through the use of discrete chaotic maps, enabled the development of simpler hardware implementations of ciphers with promising reductions in power and cost and increased performance. This work presents the Field-programmable Gate Array (FPGA) implementation of a simultaneous permutation-diffusion chaotic encryption scheme utilizing a discrete-space chaotic map. The FPGA implementation of the cipher is analyzed considering area, maximum frequency, and power consumption, and comparisons are made with the AES. The proposed algorithm has a satisfactory trade-off between area, power and performance, obtaining a peak throughput 59% higher than state-of-the-art symmetric ciphers in the literature. Thus, the proposed cipher shows that chaotic ciphers are viable for both high-performance and low-power embedded devices. Tests verified the security of the proposed cipher against statistical, differential, brute-force, and chosen plain-text attacks. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Cryptography

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Analyzing Patterns of Violence Against Women in Pernambuco Using Self-Organizing Maps and Apriori Algorithm

Analyzing Patterns of Violence Against Women in Pernambuco U...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Da Silva, Brenda Barros Alves Pereira, Rodolfo Moreira De Oliveira Rodrigues, Cleyton M. De Araujo Fagundes, Roberta Andrade Polytechnic School of Pernambuco POLI/UPE Graduate Program in Computer Engineering Recife Brazil

ISBN: (纸本)9798350374575

This study investigates significant patterns of violence against women in Pernambuco using Self-Organizing Maps (SOM) and the Apriori algorithm. The methodology includes trend analysis, clustering, and association rule mining, utilizing data from the Ministério da Mulher covering 2015 to 2021. The exploratory data analysis identified demographic, temporal, and spatial trends in violence. SOM was employed for dimensionality reduction and clustering, revealing three clusters representing 5.24%, 19.68%, and 75.08% of the dataset, respectively. The Apriori algorithm was applied to yearly subsets of each cluster to uncover relevant association patterns. Our findings highlight key characteristics and temporal dynamics of violence, supporting the development of targeted interventions and support systems. © 2024 IEEE.

关键词： Self organizing maps

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Compact Model Build Upon Dynamic Weighting Artificial Neural Network Approach for Complementary Field Effect Transistors

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IEEE Transactions on Electron Devices 2024年第1期71卷 246-253页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SPICE simulations for cost-effectiveness. This methodology is developed for gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field effect transistor (CFET), a potential candidate for future CMOS technology due to its innate properties. The critical process variation (PV) sources that severely degrade the CFET performance are estimated using DW-ANN. It reduces the computation cost and predicts the effects of PV sources with less than 1% error. Furthermore, a compact DW-ANN-based Verilog-A model has been developed that captures the dc as well as transient behavior accurately for circuit-level analysis. CFET-based circuits such as inverter, 6T-static random access memory (SRAM), and ring oscillator (RO) are characterized and implemented using DW-ANN-based CM. The overall average error of the model is reported as less than 2%. Therefore, the proposed device and circuit modeling approach provides a feasible solution for the rapid compact modeling of new emerging devices with good convergence and high accuracy. © 1963-2012 IEEE.

关键词： Neural networks

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MPEG-DASH Multi-View Video and Audio Transmission QoE Over HTTP/2 Stream

MPEG-DASH Multi-View Video and Audio Transmission QoE Over H...

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2024 International Conference on Advanced Technologies for Communications, ATC 2024

作者： Wakayama, Yamato Nunome, Toshiro Graduate School of Engineering Nagoya Institute of Technology Computer Science Program Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350353983

In this paper, we consider multi-view video and audio streaming using MPEG-DASH, which enables to transmit video tailored to the network conditions over HTTP communication. This paper uses HTTP/2 instead of HTTP/1.1, which the authors previously used. HTTP/2 manages a series of request-response exchanges called a stream, which is assigned a unique stream ID. We perform a subjective experiment under various network conditions to evaluate application-level QoS and QoE. From the evaluation results, we investigate the effect of the HTTP/2 stream on the video and audio quality of the users in the multi-view video transmission scenario. © 2024 IEEE.

关键词： Audio streaming

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QoE Comparison between Multi-User OFDMA and Reliable Groupcast for Wireless LAN Audiovisual Transmission

QoE Comparison between Multi-User OFDMA and Reliable Groupca...

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2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Deguchi, Daiki Nunome, Toshiro Graduate School of Engineering Nagoya Institute of Technology Computer Science Program Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350364866

This paper compares video and audio QoE of OFDMA multi-user transmission and reliable groupcast over wireless LAN. We assume video and audio transmission to several terminals simultaneously. As a reliable groupcast method, we employ Unsolicited Retry, a technique of IEEE 802.11aa GroupCast with Retries. We utilize IEEE 802.11ax for OFDMA transmission. We evaluate application-level QoS by computer simulation. We then assess QoE through a subjective experiment with video and audio streams generated by the output timing obtained from the simulation. We notice that each method has a situation to be applied appropriately. © 2024 IEEE.

关键词： Orthogonal frequency division multiplexing

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Design of an Automatic Price Tag System for Web-Based Retail Business 9

Design of an Automatic Price Tag System for Web-Based Retail...

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9th International Conference on Information Management and Technology, ICIMTech 2024

作者： Liawatimena, Suryadiputra Gunawan, Devina Bina Nusantara University Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Computer Science Deparment BINUS Graduate Program Master of Computer Science Jakarta11480 Indonesia Bina Nusantara University Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

Modern retail businesses face a significant challenge with the inefficiency of manually changing price labels on shelves. This manual process not only consumes valuable time and resources but also increases the likelihood of errors, leading to potential inaccuracies in pricing and a less streamlined shopping experience for customers. The proposed solution is the implementation of an Electronic Shelf Label (ESL) system that automatically displays the prices of goods on retail business shelves. This system connects a website (front end and back end) to e-paper via a Wi-Fi network and microcontroller, allowing retail business owners to update prices more easily. Additionally, buyers can search for desired items through the website. The results are the time to send data from the website to the e-paper, namely, to know the performance of the e-paper used. The average time required from 10 attempts to send data from the website to the e-paper is 20.935 seconds. Since the data is connected to the server and will be updated automatically, using this system will be more efficient than manually changing the price label, although it takes time to transfer data from the website to the e-paper. © 2024 IEEE.

关键词： Sales

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Quality Analytics for Latin American and Brazilian Robotics Symposiums 16

Quality Analytics for Latin American and Brazilian Robotics ...

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16th Brazilian Symposium on Robotics and 15th Workshop on Robotics in Education, SBR-WRE 2024

作者： Garcia Gonçalves, Luiz Marcos Electrical and Computer Engineering Graduate Program Universidade Federal do Rio Grande do Norte Natal Brazil

ISBN: (纸本)9798350391084

We bring historical findings related to the most important Latin American and Brazilian Robotics Symposiums including their quality analytics regarding all papers published since their creation. For this quality analysis, we first provide a little of history and then we apply a methodology based on a systematic mapping of the literature using Scopus (from Elsevier) and Web of Science. The quality analysis includes variables as citations metrics, and also other historical variables as participation per countries, per states, per universities, and contributed areas among others. We use metadata and tools available in the most commonly used digital libraries, for a fair comparison. To the end, with basis on the results of our methodological approach, we point out that the community has followed the right path for establishing a high quality event, mainly regarding the decision of publication of the proceedings at IEEE Xplore, and recently in the Brazilian computer Society Library (Sol-SBC), all together. Also, our analysis corroborate to verify the modi operandi that have been used in the events execution, including joining in the Workshop of Robotics in Education (WRE) and the competitions (RCB, OBR, MNR, CBR, LARC). Besides happening jointly, each event keeps their original event structure and characteristics. ©2024 IEEE.

关键词： Taxonomies

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An Expanded Latent Space Autoencoder for Land Cover Classification of Remote Sensing Images from EuroSAT 16

An Expanded Latent Space Autoencoder for Land Cover Classifi...

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16th Brazilian Symposium on Robotics and 15th Workshop on Robotics in Education, SBR-WRE 2024

作者： Vilar Oliveira, Emerson Garcia Gonçalves, Luiz Marcos Graduate Program in Electrical and Computer Engineering Universidade Federal do Rio Grande do Norte Natal Brazil

ISBN: (纸本)9798350391084

Image classification has been instrumental in the interpretation and labeling of images in the field of remote sensing, computer vision, and in robotics applications. Machine learning and artificial intelligence algorithms, particularly artificial neural networks, are extensively utilized for this purpose. In this work we propose the Expanded Latent Space Autoencoder (ELSA) with a case use application to classify land cover data. The main idea on the ELSA network structure is to utilize the latent spaces of multiple internal autoencoders in order to create an expanded latent space. This expanded latent space extracts more information from the input data, and serves as input features for a more simpler classifier network. In order to evaluate the proposed network’s ability to extract features and classify complex and multispectral images we employed it to the EuroSAT dataset. The results demonstrate a remarkable capacity for feature extraction using the ELSA network, with lower complexity, trained with a reduced number of images. The classifier network achieved a final accuracy of 98.7%, matching or exceeding the performance of more complex state-of-the-art models. ©2024 IEEE.

关键词： Neural networks

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Real Time Chest X-Ray Interpretation Applying Vision Transformer for Tuberculosis Detection

Real Time Chest X-Ray Interpretation Applying Vision Transfo...

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2024 International Conference on computer engineering, Network and Intelligent Multimedia, CENIM 2024

作者： Irhamsyah, Muhammad Roslidar Yunidar Al Lail Qadrillah, M. Nasaruddin Arnia, Fitri Munadi, Khairul Universitas Syiah Kuala Post Graduate Program in Engineering Banda Aceh2311 Indonesia Faculty of Engineering Department of Electrical and Computer Engineering 2311 Indonesia

ISBN: (纸本)9798350368802

Tuberculosis (TB) is an infectious disease that can attack the lungs and other organs. In the diagnosis of TB, the interpretation of X-ray radiological images requires special skills from medical specialists. However, the lack of experience of medical personnel and focus on X-ray examinations can be a challenge for radiologists because it has the potential to cause diagnostic errors in image interpretation. Therefore, we proposed a web-based application of real-time chest X-ray interpreter by integrating the deep learning model of Vision Transformer (ViT) to interpret chest X-ray images. The inference model was trained and tested on 652 normal and 652 tuberculosis X-ray images. The data preprocessing of Contrast Adaptive Histogram Equalization (CLAHE) was implemented to increase chest X-ray image contrast as well as inference model performance. The proposed real time system can inteprete the tested chest x-ray images with an accuracy of 95% and with simulation duration time of 4.7 seconds. © 2024 IEEE.

关键词： Diagnosis

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