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All-optical tunable integrator based on microring resonator assisted by GST superlattice 2

All-optical tunable integrator based on microring resonator ...

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2nd international conference on Optical Communication and Optical Information Processing, OCOIP 2024

作者： Zhong, Wentao Dong, Yida Shen, Mei Lei, Lei Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province Shenzhen518060 China China College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China Academy for Advanced Interdisciplinary Studies Department of Materials Science and Engineering Southern University of Science and Technology Shenzhen518000 China

ISBN: (数字)9781510688995

ISBN: (纸本)9781510688988

This paper presents the design and simulation analysis of a tunable optical integrator based on ZnS-SiO2/Ge2Sb2Te5 superlattice (GST-SL) phase change material (PCM). The transfer function of the integrator is realized through a silicon microring resonator cladded with a three-layer GST-SL (GST-SL3-MRR). The integration of the PCM into the microring resonator enables a reconfigurable Q-factor, allowing for tunable integration orders between 0.5th and 1st. Through laser-induced phase transitions between amorphous and crystalline states, the transmission spectrum of the MRR can be dynamically adjusted. Simulation results show that the integration time window reaches 300 ps for the first-order integration, and the tunable integration results closely align with the ideal mathematical predictions. demonstrating the device's highly tunable performance. Further simulations of applications for quickly solving ordinary differential equations highlight the potential applications of our device in areas such as optical signal processing and image recognition. © 2025 SPIE.

关键词： Zinc Selenide

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Air-Fuzz: Feasibility Analysis of Fuzzing-based Side-Channel Information Leakage Attack in Air-Gapped Networks 25th

Air-Fuzz: Feasibility Analysis of Fuzzing-Based Side-Channe...

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25th international conference on Information Security Applications, WISA 2024

作者： Kim, Yeon-Jin Park, Na-Eun Lee, Il-Gu Sungshin Women’s University 2 Bomun-ro 34da-gil Seongbuk-gu Seoul02844 Korea Republic of

ISBN: (纸本)9789819616237

As the number of cyberattacks via networks increases, air-gapped networks that are physically isolated from the internet are recommended to protect systems and industrial facilities. However, previous research has highlighted the possibility of data exfiltration attacks in air-gapped environments by exploiting computer systems or peripheral devices. Consequently, research to identify potential attack types and vectors in air-gapped environments is required. This study proposes an attack model that uses fuzzing on internet of Things connectivity devices to exfiltrate data within an air-gapped environment through side-channel signal patterns. We conducted an experiment to verify the feasibility of the attack model in a noisy channel and compared its performance with that of conventional attack models affected by interference and noise. By injecting Gaussian noise into wireless signals encoded with data, we compared the Bit Error Rate (BER) of the proposed attack model with that of conventional models. The BER of the proposed attack model was improved by approximately 59.43% compared with that of conventional attack models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Information leakage

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Optical tunable differentiator based on microring resonator assisted by low-loss superlattice phase change material 2

Optical tunable differentiator based on microring resonator ...

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2nd international conference on Optical Communication and Optical Information Processing, OCOIP 2024

作者： Wu, Ziqi Dong, Yida Zhong, Wentao Shen, Mei Lei, Lei Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province Shenzhen518060 China 518060 China College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China Academy for Advanced Interdisciplinary Studies Department of Materials Science and Engineering Southern University of Science and Technology Shenzhen518000 China

ISBN: (数字)9781510688995

ISBN: (纸本)9781510688988

This paper presents a novel microring resonator (MRR)-based all-optical tunable temporal differentiator. By modulating the crystallinity of the ZnS-SiO2/Ge2Sb2Te5 (GST-SL) phase change material (PCM), the coupling regime of the MRR can be precisely adjusted, achieving a differentiation order (α) range of 0.7-1.3. Experimental validation with non-return-to-zero (NRZ) and return-to-zero (RZ) signal types demonstrates a strong alignment with theoretical models, maintaining an error margin below 7.3%, which confirms the device's high adjustability and stability. The proposed tuning mechanism enables low-energy, high-speed optical control of MRR states, contributing to optimized chip area and power consumption. Supported by the unique characteristics of the superlattice structure, this all-optical tunable differentiator offers promising potential for large-scale AI-driven photonic integrated circuits, particularly in applications such as optical analog computing, optical image processing, and optical neural networks. © 2025 SPIE.

关键词： Photonic integrated circuits

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A Triangular Stable Node Network based on Self-supervised Learning for personalized prediction

A Triangular Stable Node Network based on Self-supervised Le...

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2025 IEEE international conference on Acoustics, Speech, and signal Processing, ICASSP 2025

作者： Liu, Qing Gao, Qian Fan, Jun Zhang, Zhiqiang Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Qilu University of Technology Shandong Academy of Sciences Jinan250014 China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology Shandong Academy of Sciences Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan250014 China China Telecom Digital Intelligence Techonology Co Ltd. No.1999 Shunhua road Shandong Jinan250101 China

ISBN: (纸本)9798350368741

In recent years, research has illuminated the potency of implicit data processing in enhancing user preferences. Nevertheless, barriers remain in breaking through the constraints of implicit information. This study aims to bridge this gap by firstly constructing a triangular stable node network model, tailored to manage implicit information with precision. Recognizing the challenge of pinpointing novel structures within large-scale graphs, we propose SLTSNN-a triangular stable node network based on self-supervised learning for personalized prediction. SLTSNN innovates by maximizing mutual information between graph-level and patch-level representations, while augmenting graph representations through extended enhanced representations. Additionally, it incorporates triangular data associations and introduces a triangular allocation attention network, which emphasizes strongly correlated preference features among similar users. Furthermore, SLTSNN employs contrastive learning to maximize mutual information between graph vectors and hidden representations, distinguishing between high-order global and local representations. The model's effectiveness in enhancing user preferences and capturing new graph structures is evidenced by its performance on hit rate and normalized discounted cumulative gain metrics across three datasets. © 2025 IEEE.

关键词： graph contrastive learning graph neural networks recommender systems self-supervised learning

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Linear operators for filtering digital images based on two-dimensional local spline of the fifth order 3

Linear operators for filtering digital images based on two-d...

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3rd international conference on Cyber Hygiene and Conflict Management in Global Information Networks, CH and CMiGIN 2024

作者： Prystavka, Pylyp Cholyshkina, Olha Dyriavko, Oleh National Aviation University Liubomyra Huzara Ave. 1 Kyiv03058 Ukraine Interregional Academy of Personnel Management Frometivska Str. 2 Kyiv03039 Ukraine

The paper explores the development and application of linear operators for filtering digital images, particularly through the use of fifth-order polynomial splines. The authors emphasize the importance of high-quality, high-speed image processing in enhancing cybersecurity systems, which require accurate and real-time data analysis for applications such as military intelligence and UAV navigation. They propose using B-splines, which offer precise approximation capabilities while maintaining computational efficiency. The paper outlines a method for representing these splines in a manner that reduces computational complexity, making them suitable for real-time processing in environments with high data throughput demands. The research highlights the advantages of using wider window filters and linear operators to maintain image accuracy and fidelity. It demonstrates how these techniques can be effectively applied to a range of signal processing tasks beyond image filtering, including audio and telecommunications. The experimental results presented in the paper indicate that the proposed filters significantly improve the detection and accuracy of special points in digital images, which is crucial for UAV navigation and other critical applications. The authors conclude that the use of these advanced filtering techniques can lead to more efficient and sophisticated image processing systems, with potential applications across various fields. In addition to the practical applications, the paper also discusses the theoretical underpinnings of splinebased filters, including the derivation of low- and high-frequency filter masks. The authors propose that these filters can be used to perform both sub-band filtering and multi-scale analysis of digital images, leading to improved data processing and analysis capabilities. The research contributes to the ongoing development of efficient image processing techniques that are essential for modern technology and various real-time appl

关键词： Wiener filtering

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FUGAN: A GAN based Facial Reconstructor for Accurate Unveiling of Hidden Faces 27th

FUGAN: A GAN Based Facial Reconstructor for Accurate Unveili...

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27th international conference on Pattern Recognition, ICPR 2024

作者： Sadhukhan, Mrinmoy Bhattacharya, Indrajit Dutta, Paramartha Department of Computer and System Sciences Siksha Bhavana Visva Bharati Bolpur India Department of Computer Applications Kalyani Government Engineering College Kalyani India

ISBN: (纸本)9783031781711

image-to-image translation has become a prominent trend in the field of computer vision. This innovative technique is widely employed for generating concealed facial features from given noise. It proves particularly useful in reconstructing obscured facial regions covered by masks. The underlying technology at the core of this method is the Generative Adversarial Network (GAN). The primary mechanism of GAN-based neural networks relies on an encoder-decoder structure combined with a discriminator network. The discriminator plays a crucial role in training the network to distinguish between authentic and generated images. FUGAN, a novel approach in this domain, incorporates a self-attention block and has demonstrated superior performance to other models. With an impressive SSIM and BRISQUE score of 0.928 and 27.990, respectively, FUGAN is at the forefront of achieving state-of-the-art results. The architecture of the FUGAN neural network is built upon the UNET framework, with modifications to enhance its effectiveness. These modifications involve increasing the network depth and incorporating batch instance normalization as a regularizer to achieve the desired outcomes. The resulting model attains a smaller size and exhibits high accuracy in image regeneration. This streamlined and efficient FUGAN model is well-suited for deploying low-resource internet of Things (IoT) devices. Its capability to regenerate facial features from masked regions makes it instrumental in surveillance systems, detecting individuals wearing masks and reconstructing their facial details. Github link (FUGAN: https://***/mrinmoy-sadhukhan/FUGAN-model) of our work is provided. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Gallium nitride

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Smoke Segmentation Improvement based on Fast Segment Anything Model with YOLOv11 for a Wildfire Monitoring System

Smoke Segmentation Improvement Based on Fast Segment Anythin...

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10th international conference on internet of Things, Big Data and Security, IoTBDS 2025

作者： Bunpleng, Puchit Thunyatada, Puthtipong Aksornsuwan, Bhutharit Tungpimolrut, Kanokvate Murata, Ken T. Sirindhorn International Institute of Technology Thammasat University Pathum Thani Thailand NECTEC National Science and Technology Development Agency Pathum Thani Thailand National Institute of Information and Communications Technology Tokyo Japan

ISBN: (纸本)9789897587504

Forests and wildlife are crucial parts of our ecosystem. Wildfires occurring in dry and hot regions represent a significant threat to these areas, particularly in ASEAN countries during the dry season. While human observers are often employed to detect wildfires, their scarcity and limited availability highlight the need for automated solutions. This study explores the use of machine learning, specifically computer vision, to enhance wildfire detection by segmenting smoke, an approach which potentially gives information regarding the size and the direction of the spread of the smoke, aiding mitigation efforts. We extend prior work by proposing a model to predict the errors and performance of segmentation masks without access to the ground truth, with the aim of facilitating iterative self-improvement of segmentation models. The FireSpot dataset is used to fine-tune a YOLOv11 model to predict bounding boxes of smoke successfully;subsequently, the outputs of this model are used as a prompt to refine a FastSAM model designed to segment the image into a proposed mask containing the smoke. The proposed mask and the corresponding original image are then used to train a machine learning model where the targets are metrics regarding the error rates of the masks. The results show that a gradient boosting model achieves good prediction performance in predicting some error metrics like the IoU (denoted TPP in this paper) between the proposed and actual segmentation masks with an MSE of 0.03 and R2 of 0.46, as well as the proportion of false positives over the union of the proposed and actual masks (denoted FPP in our paper) with an MSE of 0.0002 and R2 of 0.95, while a pre-trained deep learning model fails to learn the distribution, achieving considerably lower performance for IoU with an MSE of 0.05 and R2 of 0.06 and FPP with an MSE of 0.0002 and R2 of -1.15. These findings open the way to future work where the results of the error prediction model can be used as feedback to

关键词： Deep learning

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Proceedings - 15th international conference on signal image technology and internet based systems, SISITS 2019

Proceedings - 15th International Conference on Signal Image ...

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15th international conference on signal image technology and internet based systems, SISITS 2019

ISBN: (纸本)9781728156866

The proceedings contain 106 papers. The topics discussed include: shot detection in racket sport video at the frame level using a recurrent neural network;low-light image enhancement via adaptive shape and texture prior;image sharpening by grid warping with curvature analysis;on the detection of video's ethnic Vietnamese Thai dance movements;human tracking for children behavior analysis in nursery schools;digital building twins - contributions of the ANR McBIM project;loop closure detection for monocular visual odometry : deep-learning approaches comparison;an adaptive background modeling method based on modified running averages;and time unification on local binary patterns three orthogonal planes for facial expression recognition.

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Medical image Noise Reduction Methods based on Cutting-Edge Hybrid Filtering Designs

Medical Image Noise Reduction Methods Based on Cutting-Edge ...

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international conference on Smart systems and Wireless Communication, SSWC 2024

作者： Saha, Tanusree Vishal, Kumar Magadh University Bodh Gaya India Department of Information Technology JIS College of Engineering Kalyani India Department of Mathematics Magadh University Bodh Gaya India

ISBN: (纸本)9789819613472

A high-resolution noise free medical image is an essential requirement for accurate disease detection. Medical image processing and analysis techniques have become utmost important in recent decades as a supplementary competence for medical professionals in the fields of diagnosis and prevention. Obtaining high-quality images without any interference is a crucial requirement for effectively managing therapeutic images. Medical images may contain many types of noises for involvement of simultaneous operation of multiple equipment involved in data capturing and transmission. Various filters have been suggested for eliminating different types of noises, each having its own merits and drawbacks depending on its capabilities and projected benefits. Our research depicts a technique for removing noises from medical images using a hybrid filtering approach based on ensemble adaptive mean filtering and Block-matching-3D filtering. The proposed methodologies specifically aim to reduce the speckle noise in brain MRI images obtained from ultrasonic therapy by employing hybrid filtering techniques. This proposed hybrid filtering algorithms integrate the most effective aspects of high-performance filters to achieve a de-noised image that retains fine details, edges, and textures. The statistical performance measurement metrics like Root Mean Square Error (RMSE), Peak signal-to-Noise Ratio (PSNR) are employed to evaluate the improved visual quality of the images. The results indicate that our proposed hybrid filtering technique functioning efficiently and provide better quality de-noised image compare with other existing de-noising techniques. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： image enhancement

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A New Method of Integrated Radar-Communication System Waveform Design and signal Processing based on OFDM Block Subcarrier Allocation 9th

A New Method of Integrated Radar-Communication System Wavefo...

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9th international conference on Intelligent IoT as a Service

作者： Xu, Zhan Quan, Cong Zhu, Weige Yang, Xiaolong Beijing Informat Sci & Technol Univ Sch Informat & Commun Engn Beijing 100071 Peoples R China Shanghai Inst Satellite Engn Shanghai Peoples R China

ISBN: (纸本)9783031705069;9783031705076

In the context of the internet of Vehicles (IoV) and sixth-generation (6G) wireless communication, wireless radar and communication (RadCom) systems face the dual challenges of improving spectrum utilization efficiency and lowering interference levels. The use of orthogonal frequency division multiplexing (OFDM) signals in a shared waveform system has the potential to mitigate mutual interference between communication and radar while also meeting the need for improved range resolution. Some researchers have proposed using the odd and even carriers of OFDM signals to modulate radar and communication functions, intending to achieve integration. Nevertheless, this methodology presents several concerns, such as the potential for interference between radar carriers and communication carriers and the negative impact caused by the cyclic prefix (CP) on radar performance. This study presents a new method that leverages OFDM and block subcarrier allocation techniques to enhance the integration of radar and communication system performance. The primary objective is to mitigate interference by consolidating radar and communication subcarriers while minimizing the detrimental effects of CP on radar performance by utilizing zero padding (ZP) as a replacement for CP. Furthermore, this method reduces pilot tone costs by utilizing radar data to estimate Doppler frequency offsets. It can dynamically adjust the number of radar and communication subcarriers to accommodate evolving performance demands. Simulation results indicate that in the presence of residual frequency offset, this solution enhances communication performance while slightly degrading radar performance.

关键词： RadCom OFDM Block Subcarrier Allocation

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