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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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Light Source Attacks on CMOS-Based QRNGs 4

Light Source Attacks on CMOS-Based QRNGs

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4th International Computational Imaging conference, CITA 2024

作者： Zhang, Beibei Li, Lang xu, Yuehan Wang, Tao Zeng, Guihua State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781510688834

QRNGs, which leverage quantum mechanical principles to generate random numbers, are widely utilized in information security and cryptography. This paper reviews various QRNG systems and their evolution, with a particular focus on the simple and efficient CMOS-based QRNG system. However, while current random number generation methods ensure randomness, they do not guarantee the security of the generated random numbers, especially in encryption applications. The results demonstrate that an attacker can manipulate the light source to inject attack signals, leading to an increase in the entropy value calculated by legitimate users. This allows the attacker to extract additional entropy information. Notably, the compromised random numbers still pass the NIST randomness tests, indicating a fundamental breach of the system's security. This paper proposes strategies for identifying and defending against such potential attacks, with the aim of enhancing the reliability and security of QRNG systems. © 2025 SPIE.

关键词： CMOS integrated circuits

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Intelligent IoT-Driven advanced Predictive Maintenance System for Industrial applications

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SN Computer Science 2025年第2期6卷 1-24页

作者： Dhinakaran, D. Edwin Raja, S. Velselvi, R. Purushotham, N. Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Chennai India Department of Computer Science and Engineering P.S.R Engineering College Sivakasi India Department of CSE School of Computing Mohan Babu University Tirupati India

Predictive Maintenance (PdM) aims to ensure the continuous operation of high-risk industrial systems. This challenge is especially critical in environments where equipment failure can cause major financial losses and disrupt operations. Traditional PdM approaches, while fairly effective, often fall short in accurately predicting failures due to their reliance on simple statistical methods and predefined rules. The proposed work introduces an Intelligent IoT-Driven advanced Predictive Maintenance System (APdM) that addresses these limitations. By integrating advanced machine learning techniques, including supervised and reinforcement learning, with IoT technologies to enhance predictive accuracy as well as the operational efficiency. The system leverages Explainable AI (xAI) to ensure transparency in decision-making and employs federated learning for distributed model training, preserving data privacy across multiple edge devices. The proposed APdM system was evaluated using the Kaggle "Air Compressor Predictive Maintenance" Dataset, which provided extensive sensor data from heavy vehicle operations. Comparative analysis against four prevailing PdM approaches—Traditional PdM, Decision Support System-PdM, Genetic Algorithm-based PdM, and AI-based PdM—demonstrated the superior performance of our system. The results show that the APdM system, powered by intelligent IoT integration, diminishes the Mean Error Percentage (MEP) by up to 38.4% compared to traditional methods and decreases the Mean Absolute Error (MAE) by 36.7% relative to DSS-PdM. Additionally, the system achieves a 78% improvement in Symmetric Mean Absolute Percentage Error (SMAPE) over GA-PdM, underscoring its robust performance in real-world industrial scenarios. These outcomes validate the effectiveness of the proposed APdM system, marking a significant improvement in the field of predictive maintenance through the intelligent integration of IoT technologies. © The Author(s), under exclusive licence to S

关键词： Explainable AI IoT Machine learning Predictive maintenance Supervised and reinforcement learning

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sensor-Agnostic Graph-Aware Kalman Filter for Multi-Modal Multi-Object Tracking 27th

Sensor-Agnostic Graph-Aware Kalman Filter for Multi-Modal Mu...

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27th International conference on Pattern Recognition, ICPR 2024

作者： Sani, Depanshu Iyer, Anirudh Rai, Prakhar Anand, Saket Srivastava, Anuj Kalyanaraman, Kaushik IIIT-Delhi New Delhi India Florida State University Tallahassee United States

ISBN: (纸本)9783031784439

Recent progress in open-source object detection techniques has significantly advanced Multi-Object Tracking (MOT) methodologies, primarily under the tracking-by-detection paradigm. To enhance the robustness and reliability of MOT systems, recent research has proposed integrating information gathered from diverse sensors. However, many Kalman filter-based MOT approaches assume the independence of object trajectories, overlooking potential inter-object relationships. While some efforts have been made to incorporate these relationships, they often concentrate on learning feature representations to facilitate better association. Moreover, the existing filter-based method for estimating graphs from noisy data is unsuitable for online MOT applications. To alleviate these problems, we introduce a sensor Agnostic Graph-Aware (SAGA) Kalman filter, which is the first online state estimation technique designed to fuse multi-modal graphs derived from noisy multi-sensor data. We validate the effectiveness of our proposed framework through extensive experiments conducted on both synthetic and real-world driving dataset (nuScenes). Our results showcase an improvement in MOTA and a reduction in estimated position errors (MOTP) and identity switches (IDS) for tracked objects using the SAGA-KF. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Kalman filters

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Demodulation Method for Optical Fiber Flow Velocity sensor Based on Reference Filter 4

Demodulation Method for Optical Fiber Flow Velocity Sensor B...

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4th International Computational Imaging conference, CITA 2024

作者： Zhang, xingyu Chen, Zhiyuan xu, Ronghui Yang, Tianyu Liu, Huanhuan Dong, Yuming Department of Optoelectronic Engineering Guilin University of Electronic Technology Guilin541004 China Opto-Electronic Engineering and Technology Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9781510688834

This paper proposes a demodulation method for GaAs fiber-optic flow velocity sensors based on convolution operations. The method employs a five-layer wavelet forced denoising technique to smooth the acquired spectral data and utilizes a long-pass filter (LPF) waveform as a reference baseline for wavelength drift demodulation via convolution. Through polynomial fitting, this demodulation approach reduces demodulation errors and further enhances accuracy. Within the flow rate measurement range of 1.7 to 42.5 cm/s, the sensor exhibits a maximum flow rate sensitivity of 97.3 pm/(cm/s), with wavelength demodulation accuracy reaching the picometer level. The minimum flow rate demodulation error is as low as 0.02 cm/s. This method is capable of delivering high-precision demodulation across various application scenarios, demonstrating significant potential for applications in the field of fiber flow rate sensing. © 2025 SPIE.

关键词： Flow velocity

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A Versatile, Low-Cost Robotic System for Educational applications

A Versatile, Low-Cost Robotic System for Educational Applica...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Phillips, Joseph M. Monroe, Charles Shue, Sam Conrad, James M. Unc Charlotte CharlotteNC United States

ISBN: (纸本)9798331504847

The rising cost of robotic platforms has created significant challenges for engineering students and academic institutions. High prices often make these platforms unaffordable for students, limiting their access to hands-on experience in robotics. Similarly, schools face financial strain in maintaining and upgrading such systems, which can hinder their ability to provide quality education in robotics and automation. This issue has become particularly pressing as robotics plays a critical role in engineering and technology curriculum. A solution to these issues is a low-cost, low-power robotic system that balances affordability with advanced functionality. A platform is needed that integrates essential features such as ROS (Robot Operating System), LiDAR, motor control, and camera vision, providing a comprehensive tool-set for learning and experimentation. Furthermore, the system should support simple functionality for beginners, but also be able to accommodate students wanting to progress to advanced robotic applications. This paper explores the design and development process of this robotic platform, highlighting its modular design, affordability, and versatility. © 2025 IEEE.

关键词： Robot Operating System

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Reconfigurable Ge2Sb2Te5/MoS2 Heterojunction Photodetector with High-Contrast Responsivity for Retinomorphic Vision Sensing

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advanced OPTICAL MATERIALS 2025年

作者： Wang, Yu Zhou, Yang Mu, Haoran Chen, Youchen Yang, Miaomiao Zhao, Zhenhe Zhang, Ke Zhang, Congwen xia, xue Chen, Weiqiang Lin, Shenghuang Songshan Lake Mat Lab Dongguan 523808 Guangdong Peoples R China South China Normal Univ Coll Biophoton Sch Optoelect Sci & Engn MOE Key Lab Laser Life Sci Guangzhou Guangdong Peoples R China South China Normal Univ Coll Biophoton Sch Optoelect Sci & Engn Guangdong Prov Key Lab Laser Life Sci Guangzhou Guangdong Peoples R China South China Normal Univ Coll Biophoton Sch Optoelect Sci & Engn Guangzhou Key Lab Spectral Anal & Funct Probes Guangzhou Guangdong Peoples R China

Reconfigurable photodetectors are crucial for applications such as adaptive sensing and dynamic imaging. However, conventional devices based on materials such as silicon typically require external electric fields and additional memory units, resulting in increased system complexity and energy consumption. Here, a self-driven, reconfigurable, and controllable photoresponse with a large responsivity contrast of up to 100 is achieved using a Ge2Sb2Te5 (GST)/MoS2 heterojunction, leveraging the integration of the reversible phase-transition capability of phase-change materials (PCMs) with the nonvolatile reconfigurable optoelectronic merits of two-dimensional (2D) materials. The reconfigurable GST/MoS2 heterojunction photodetector also demonstrates fast response times, excellent cycling stability, and a linear photocurrent-power relationship, supporting its use in real-time imaging systems. Furthermore, a 3 x 3 reconfigurable photodetector array is implemented as an optical convolution kernel for in-sensor image processing, achieving high-quality image recognition, contrast enhancement, and edge detection. This work positions phase-change-2D heterojunctions as a promising platform for next-generation reconfigurable photodetection and intelligent sensing technologies.

关键词： 2D photodetectors convolution phase-change materials visual sensor

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Low-frequency spring-like MEMS for photoacoustic trace gas detection 24

Low-frequency spring-like MEMS for photoacoustic trace gas d...

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2025 conference on MOEMS and Miniaturized systems

作者： Dello Russo, Stefano Pelini, Jacopo Garcia, Inaki Lopez Galli, Iacopo Pastor, Pablo Cancio Canino, Maria Concetta Roncaglia, Alberto De Natale, Paolo Borri, Simone de Cumis, Mario Siciliani ASI Agenzia Spaziale Italiana Ctr Geodesia Spaziale I-75100 Matera Italy CNR INO Ist Nazl Ott Largo E Fermi 6 I-50125 Florence Italy LENS Via N Carrara 1 I-50019 Sesto Fiorentino FI Italy Univ Naples Federico II Corso Umberto I 40 I-80138 Naples Italy Consiglio Nazl Ric CNR Ist Microelettron & Microsistemi IMM Zona Ind Ottava Str 5 I-95121 Catania Italy Consiglio Nazl Ric CNR Ist Microelettron & Microsistemi IMM Via P Gobetti 101 I-40129 Bologna Italy

ISBN: (数字)9781510685130

ISBN: (纸本)9781510685123;9781510685130

Studies on gas trace spectroscopy have intensified considerably in recent years due to the great demand for reliable sensors in the quantification of gas concentrations in various fields, including environmental monitoring, medical sensors, early fire detection, and security control. Among various approaches, photoacoustic spectroscopy (PAS) is promising due to wavelength independence, zero background, and small investigating volumes. In this context, we report the realization and implementation of a new low-frequency, spring-like Micro Electro Mechanical System (MEMS) acting as a microphone in a PAS setup. The MEMS behaviors were studied experimentally both in amplitude and frequency modulation, analyzing the figures of merit (FOM) of each approach. Finally, a long-term stability analysis is also reported to exploit the ultimate detection limits achievable with each approach.

关键词： Cantilever-enhanced photo-acoustic spectroscopy (CEPAS) MID-IR sensing Spectrophones Trace-gas photo-acoustic sensor

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RDM: A Light Field Super-Resolution Model Improved with Retinex Decomposition 16

RDM: A Light Field Super-Resolution Model Improved with Reti...

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16th International conference on Signal Processing systems, ICSPS 2024

作者： Lyu, Wenqi Ke, Wei Sheng, Hao Ma, xiao Liu, Lixue Faculty of Applied Sciences Macao Polytechnic University China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China

ISBN: (纸本)9781510689251

Light field cameras hold significant value in applications such as depth estimation, 3D video acquisition, and image super-resolution. Compared to traditional single-image super-resolution methods, light field images can capture object information from multiple spatial and angular perspectives, which is more conducive to capturing detail information. However, current advanced light field super-resolution models still exhibit issues like blurriness, jaggedness, and dimness in 4x light field super-resolution. To address this, we propose a novel light field super-resolution framework that utilizes the Retinex decomposition concept to solve common problems such as ghosting and overlap, thereby improving image quality. By decomposing the light field image into illumination and reflection components and processing them separately, our model significantly enhances detail preservation and color consistency. Experimental results on multiple datasets demonstrate that our model exhibits outstanding performance, both subjectively and objectively, highlighting the effectiveness of this framework and its broad application potential in the field of computational imaging. © 2025 SPIE.

关键词： Image acquisition

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Defense Strategy Security Mechanism for sensor Networks 5th

Defense Strategy Security Mechanism for Sensor Networks

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5th EAI International conference on Cognitive Computing and Cyber Physical systems, IC4S 2024

作者： Nayak, Rakesh Shinde, Jitesh Gupta, Praveen Dash, Satyabrata Ghugar, Umashankar Singh, Lokendra Department of CSE OP Jindal University Raigarh India India Visakhapatnam India Uttrakhand Dehradun India Department of Computer Science and Engineering Jaipur National University Jaipur India

ISBN: (纸本)9783031770746

This paper examines the safety measures used in sensing unit networks, focusing on their effectiveness in securing critical applications from threats like unapproved access, information violations, and meddling. It assesses the current state of these devices, identifies their weaknesses and strengths, and identifies obstacles such as source restrictions, scalability, and ease of access to risks. The paper emphasizes the importance of cooperation and data sharing among countries in reinforcing protection technique safety devices. The review concludes with a call to action, emphasizing the need for continuous research, innovation, and policy frameworks to address the evolving security landscape and protect critical infrastructure. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Network intrusion

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