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15th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2023

作者： Olasiman, Mara Mae M. Librado, Lester G. Pao, Jeanette C. Baldonado, Faith Q. Banglos, Charles Alver G. Paradela, Immanuel P. Salaan, Carl John O. Department of Electrical Engineering Philippines Department of Computer Engineering and Mechatronics Philippines College of Engineering Department of Mechanical Engineering Philippines Graduate School of Engineering Mindanao State University - Iligan Institute of Technology Iligan City9200 Philippines

ISBN: (纸本)9798350381177

Flash flood is a naturally occurring calamity, espe-cially in tropical countries like the Philippines. The wreckage and grief caused by catastrophic typhoons emphasized the need for an Early Warning System (EWS) specifically for flash flood and storm surge applications. This study focuses on the development of an EWS enclosed in a buoy that will operate by floating along the highland rivers of flood-prone areas and sending notifications to disaster management authorities if a flash flood occurs. This system will be able to gather data from the behaviors of water just by observing the Euler angles - yaw ($\lambda$), roll ($\theta$), and pitch (φ) while partially submerged in the middle of a river. The main distinction between this EWS from other systems is that it is an off-grid circuit, can also be submerged in the ocean for storm surge applications, and will utilize an Inertial Measurement Unit (IMU) sensor to monitor the water behavior. Experiments done for this study confirmed the buoy's waterproof capability not only in securing the integrity of its electrical components but also by gathering Euler angles as the basis of water flow characterization. The program's data yields a graphical representation of yaw, roll, and pitch angles if the water flow is normal, disturbed, and turbulent. Hence, this system is leaning towards low power consumption given that power saving modes like deep sleep mode will be applied to the system which means that using one mode compared with another mode will result in 13.46% better power use optimization. Meanwhile, tests conducted for this study are done in a flume simulator since we can't fully simulate a flash flood. © 2023 IEEE.

关键词： Buoys

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Tailoring Fano resonance characteristics for GSS4T1-based reconfigurable photonics

Tailoring Fano resonance characteristics for GSS4T1-based re...

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2024 Frontiers in Optics, FiO 2024

作者： Foteinopoulou, Stavroula Tsitsas, Nikolaos L. Department of Electrical and Computer Engineering University of New Mexico NM87131-0001 United States School of Informatics Aristotle University of Thessaloniki Thessaloniki54124 Greece

We present a GSS4T1-based metagrating designed to exhibit a homogeneous-optical-medium response, when GSS4T1 amorphous, or a judicious Fano response, when GSS4T1 crystalline, which enables a negative beam steering tha... 详细信息

关键词： Photonics

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Design and Testing of Power-Optimized Waveforms on Next-Generation Passive RFID Tags

Design and Testing of Power-Optimized Waveforms on Next-Gene...

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Opportunity Research Scholars Symposium (ORSS)

作者： Vishnu Sivampeta Lauren Yao Katja Maywood Dharshan Senthilkumar Christopher Saetia Gregory D. Durgin School of Electrical and Computer Engineering Georgia Institute of Technology

ISBN: (数字)9798350390698

ISBN: (纸本)9798350390704

Power harvesting efficiency remains a key limiting factor for passive radio frequency identification (RFID) tags. This study aims to improve the power harvesting efficiency of next-generation RFID tags by implementing power-optimized waveforms (POWs) instead of continuous wave (CW) waveforms as the input interrogating signals to wake-up and communicate with RFID tags. A software-defined radio (SDR) is configured as a pseudo-RFID reader to generate and transmits POWs to newer RFID tags with the newer Impinj M750 and NXP U9 chips, showing that these recent chip manufacturer products are compatible with POWs. This novel method of programming an SDR could facilitate easier testing of POWs through an open-source software that streamlines POW modifications.

关键词： Legged locomotion Limiting Programming Energy harvesting RFID tags Passive RFID tags Next generation networking Open source software Testing Software radio

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H2/H∞ Dynamic Output Synthesis Based on Regularized Reinforcement Learning

H2/H∞ Dynamic Output Synthesis Based on Regularized Reinfor...

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International Conference on Control, Instrumentation, and Automation

作者： Mehrdad Rajabalifardi Mahdi Sojoodi Pouya Badri School of Electrical and Computer Engineering TMU Tehran Iran

ISBN: (数字)9798331509972

ISBN: (纸本)9798331509989

This study deals with a new method for designing a mixed ${H}_{2} / {H}_{\infty}$ dynamic output feedback controller based on reinforcement learning (RL). This paper aims to design an optimal machine learning-based controller that uses a robust and regularized reinforcement learning-based methodology to stabilize the system in the presence of disturbances. Furthermore, using the reinforcement learning algorithms, the dynamic output feedback controller is designed via policy evaluation and policy improvement steps. Eventually, the authors illustrate the advantages of the proposed methods through numerical simulations via error metrics.

关键词： Space vehicles Measurement Learning systems Machine learning algorithms Automation Heuristic algorithms Instruments Reinforcement learning Numerical simulation Output feedback

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Simulink Mutation Testing using CodeBERT

arXiv

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arXiv 2025年

作者： Zhang, Jingfan Ghobari, Delaram Sabetzadeh, Mehrdad Nejati, Shiva School of Electrical Engineering and Computer Science University of Ottawa Canada

We present BERTiMuS, an approach that uses CodeBERT to generate mutants for Simulink models. BERTiMuS converts Simulink models into textual representations, masks tokens from the derived text, and uses CodeBERT to predict the masked tokens. Simulink mutants are obtained by replacing the masked tokens with predictions from CodeBERT. We evaluate BERTiMuS using Simulink models from an industrial benchmark, and compare it with FIM – a state-of-the-art mutation tool for Simulink. We show that, relying exclusively on CodeBERT, BERTiMuS can generate the block-based Simulink mutation patterns documented in the literature. Further, our results indicate that: (a) BERTiMuS is complementary to FIM, and (b) when one considers a requirements-aware notion of mutation testing, BERTiMuS outperforms FIM. Copyright © 2025, The Authors. All rights reserved.

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Revisiting Kernel Attention with Correlated Gaussian Process Representation 40

Revisiting Kernel Attention with Correlated Gaussian Process...

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40th Conference on Uncertainty in Artificial Intelligence, UAI 2024

作者： Bui, Long Minh Huu, Tho Tran Dinh, Duy Nguyen, Tan Minh Hoang, Trong Nghia FPT Software AI Center Department of Mathematics National University of Singapore Singapore School of Electrical Engineering and Computer Science Washington State University United States

Transformers have increasingly become the de facto method to model sequential data with state-of-the-art performance. Due to its widespread use, being able to estimate and calibrate its modeling uncertainty is important to understand and design robust transformer models. To achieve this, previous works have used Gaussian processes (GPs) to perform uncertainty calibration for the attention units of transformers and attained notable successes. However, such approaches have to confine the transformers to the space of symmetric attention to ensure the necessary symmetric requirement of their GP’s kernel specification, which reduces the representation capacity of the model. To mitigate this restriction, we propose the Correlated Gaussian Process Transformer (CGPT), a new class of transformers whose self-attention units are modeled as cross-covariance between two correlated GPs (CGPs). This allows asymmetries in attention and can enhance the representation capacity of GP-based transformers. We also derive a sparse approximation for CGP to make it scale better. Our empirical studies show that both CGP-based and sparse CGP-based transformers achieve better performance than state-of-the-art GP-based transformers on a variety of benchmark tasks. © 2024 Proceedings of Machine Learning Research. All rights reserved.

关键词： Distribution transformers

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Self-Supervised WiFi-Based Activity Recognition

Self-Supervised WiFi-Based Activity Recognition

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2022 IEEE GLOBECOM Workshops, GC Wkshps 2022

作者： Bocus, Mohammud J. Lau, Hok-Shing Mcconville, Ryan Piechocki, Robert J. Santos-Rodriguez, Raul University of Bristol School of Computer Science Electrical and Electronic Engineering and Engineering Maths Bristol United Kingdom

ISBN: (纸本)9781665459754

Traditional approaches to activity recognition involve the use of wearable sensors or cameras in order to recognise human activities. In this work, we extract fine-grained physical layer information from WiFi devices for the purpose of passive activity recognition in indoor environments. While such data is ubiquitous, few approaches are designed to utilise large amounts of unlabelled WiFi data. We propose the use of selfsupervised contrastive learning to improve activity recognition performance when using multiple views of the transmitted WiFi signal captured by synchronised receivers deployed in different positions. We conduct extensive Human Activity Recognition (HAR) experiments in two furnished office rooms, whereby six participants of different age groups performed six day-to-day activities. We compare the proposed contrastive learning system with conventional non-contrastive systems and observe significant improvement on the task of WiFi based activity recognition under few-shot learning scenarios. Namely, contrastively pretraining with an AlexNet-based backbone encoder led to a 22% increase in macro F1 score when only 1.29% of labelled training samples are considered in the fine-tuning stage. © 2022 IEEE.

关键词： Learning systems

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Double-Blockchain Assisted Secure and Anonymous Data Aggregation for Fog-Enabled Smart Grid

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engineering 2022年第1期8卷 159-169页

作者： Siguang Chen Li Yang Chuanxin Zhao Vijayakumar Varadarajan Kun Wang Jiangsu Key Lab of Broadband Wireless Communication and Internet of Things Nanjing University of Posts and TelecommunicationsNanjing 210003China Jiangsu Engineering Research Center of Communication and Network Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China Anhui Provincial Key Laboratory of Network and Information Security Anhui Normal UniversityWuhu 241000China School of Computer Science and Engineering Vellore Institute of TechnologyChennai 600127India Department of Electrical and Computer Engineering University of CaliforniaLos AngelesCA 90095USA

As a future energy system,the smart grid is designed to improve the efficiency of traditional power systems while providing more stable and reliable ***,this efficient and reliable service relies on collecting and analyzing users’electricity consumption data frequently,which induces various security and privacy *** address these challenges,we propose a double-blockchain assisted secure and anonymous data aggregation scheme for fog-enabled smart grid named ***,we design a three-tier architecture-based data aggregation framework by integrating fog computing and the blockchain,which provides strong support for achieving efficient and secure data collection in smart ***,we develop a secure and anonymous data aggregation mechanism with low computational overhead by jointly leveraging the Paillier encryption,batch aggregation signature and anonymous *** particular,the system achieves fine-grained data aggregation and provides effective support for power dispatching and price adjustment by the designed double-blockchain and two-level data ***,the superiority of the proposed scheme is illustrated by a series of security and computation cost analyses.

关键词： Blockchain Fog computing Homomorphic encryption Smart grid Anonymity

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AntFuzz: Follow Ants to Find Food in network 4

AntFuzz: Follow Ants to Find Food in Network

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4th International Conference on Industrial Automation, Robotics and Control engineering, IARCE 2024

作者： Xu, Fei Wang, Zhiwei Zhang, Yuqing Wang, He School of Cyber Engineering Xidian University Xi'an China University of Academy of Sciences National Computer Network Intrusion Protection Center Beijing China Hainan University Haikou China

ISBN: (纸本)9798350380323

Fuzzer is widely employed for vulnerability discovery and security assessment of software systems. Based on existing protocol fuzzers, this paper proposes a more efficient fuzzing solution called AntFuzz. It draws inspiration from ant colony algorithms, where ants use pheromones to find food. Similarly, seeds in AntFuzz require pheromones to guide their search direction. This work introduces a seed-centric multi-factor selection strategy. Specifically, the protocol state and code coverage assist in exploring a wider code space, while the coverage of predecessor basic blocks of vulnerability blocks helps trigger vulnerabilities more rapidly. By considering the low-frequency paths, states, and vulnerability blocks that seeds reach, seeds are given different probabilities of execution and mutation. Additionally, the network sockets of the target program are modified to Unix domain sockets to increase the throughput of fuzzing. The performance of AntFuzz is validated on real-world network service programs. Preliminary evaluation results indicate that compared to AFLNET, AntFuzz achieves up to a 50x increase in throughput, an 89% increase in code coverage, and significantly earlier triggering of vulnerabilities. © 2024 IEEE.

关键词： Ant colony optimization

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Identification of Macro-Nutrient Deficiency in Onion Leaves (Allium cepa L.) Using Convolutional Neural network (CNN) 5

Identification of Macro-Nutrient Deficiency in Onion Leaves ...

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5th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2022

作者： Mateo, Kristin Clarisse H. Navarro, Laurence Kobe B. Manlises, Cyrel O. School of Electrical Electronics and Computer Engineering Mapua University Manila Philippines Philippines

ISBN: (纸本)9781665455121

In the Philippines, the onion is among the major crops produced with an estimated production of 229.50 thousand metric tons last 2020. Producing these onions relies on manpower, particularly from local farmers. However, the nutrient deficiency that the onions may have can affect the product quality and crop yield. The possible nutrient deficiency of onions may be identified based on the features of the leaves. Therefore, based on the visual symptoms, a modern approach to identifying the primary macro-nutrient deficiency in onion leaves was developed using a Convolutional Neural network with the VGG-16 architecture. The system obtained an accuracy of 60%, 76%, and 100% in identifying the macro-nutrient deficiency of onion leaves in Nitrogen, Phosphorus, and Potassium, respectively. It obtained an accuracy of 96% in determining no nutrient deficiency in onion leaves. The overall system accuracy obtained was 83%. © 2022 IEEE.

关键词： Convolutional neural networks

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