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10th international Symposium on Dependable Software engineering: theories, Tools and Applications, SETTA 2024

10th International Symposium on Dependable Software Engineer...

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10th international Symposium on Dependable Software engineering: theories, Tools and Applications, SETTA 2024

ISBN: (纸本)9789819606016

the proceedings contain 22 papers. the special focus in this conference is on Dependable Software engineering: theories, Tools and Applications. the topics include: Extending Symbolic Heap to Support Shared Ownership;constraint based Invariant Generation with Modular Operations;Data-Dependent WAR Analysis for Efficient Task-based Intermittent Computing;Can Language Models Pretend Solvers? Logic Code Simulation with LLMs;enhancing Multi-modal Regular Expression Synthesis via Large Language Models and Semantic Manipulations of Sub-expressions;Formal Verification of RISC-V Processor Chisel Designs;the Principle of Staking: Formal Verification of Staking Smart Contract;a Contract-based Framework for Formal Verification of Embedded Software;Formalizing x86-64 ISA in Isabelle/HOL: A Binary Semantics for eBPF JIT Correctness;the Design of Intelligent Temperature Control System of Smart House with MARS;universal Construction for Linearizable but Not Strongly Linearizable Concurrent Objects;Cache Behavior Analysis with SP-Relative Addressing for WCET Estimation;timing Analysis of Cause-Effect Chains for External Events with Finite Validity Intervals;runtime Verification of Neural-Symbolic systems;eidos: Efficient, Imperceptible Adversarial 3D Point Clouds;MILE: A Mutation Testing Framework of In-Context Learning systems;a Derivative-based Membership Algorithm for Enhanced Regular Expressions;nanoHook: An Efficient System Call Hooking Technique with One-Byte Invasive;faster Lifetime-Optimal Speculative Partial Redundancy Elimination for Goto-Free Programs;EDSLog: Efficient Log Anomaly Detection Method based on Dataset Partitioning.

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High-throughput Acoustic Sorting of Cellular-Sized Microparticles in 3d Microfluidic Channels 38

High-Throughput Acoustic Sorting of Cellular-Sized Micropart...

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38th ieee international conference on Micro Electro Mechanical systems, MEMS 2025

作者： Roy, Akash Neff, Baptiste Esfahani, Kianoush Sadeghian Sengupta, Anik Kim, Eun S. University of Southern California Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798331508890

this manuscript presents high-throughput sorting of cellular-sized microparticles within a three-dimensional microfluidic channel by focused bulk acoustic wave (BAW) produced by a Self-Focusing Acoustic Transducer (SFAT). the focused ultrasound induces a substantially higher acoustic radiation force within the focal region, enabling sorting based on particle size and density. Unlike surface-acoustic-wave-based setups, the BAW-based technique uses a three-dimensional microfluidic channel through which a mixture of particles is transported, while SFAT(s) may be placed at multiple points along the channel for multi-stage sorting. the technique has been successfully used in sorting 50 μm microparticles, which are analogous to cancerous or differentiated Mesenchymal Stem Cells (MSC), from 30 μm microparticles, which are analogous to healthy MSC. the sorting results in 97.5% purity at the smaller microparticle outlet and a 97.2% recovery rate for the smaller particles. the technique allows sorting 650,000 smaller and 142,000 larger microparticles within a mere 10 minutes. © 2025 ieee.

关键词： Stem cells

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Proceedings - 13th ieee international conference on Service-Oriented System engineering, SOSE 2019, 10th international workshop on Joint Cloud Computing, JCC 2019 and 2019 ieee international workshop on Cloud Computing in Robotic systems, CCRS 2019

Proceedings - 13th IEEE International Conference on Service-...

引用

13th ieee international conference on Service-Oriented System engineering, SOSE 2019, 10th international workshop on Joint Cloud Computing, JCC 2019 and 2019 ieee international workshop on Cloud Computing in Robotic systems, CCRS 2019

ISBN: (纸本)9781728114415

the proceedings contain 52 papers. the topics discussed include: comparison between chunk-based and layer-based container image storage approaches: an empirical study;mixup based privacy preserving mixed collaboration learning;GPU scheduling for short tasks in private cloud;LS4BUCC: a low overhead storage architecture for blockchain based unmanned collaborative cognition system;distributed computing in cyber-physical intelligence: robotic perception as an example;evaluating cloud microservices with DIRECTOR;a multi-task scheduling algorithm for cloud robots;undertow: an intra-kernel isolation mechanism for hardware-assisted virtual machines;effective vehicle tracking algorithm for smart traffic networks;and a service-oriented approach for assessing the quality of data for the Internet of things.

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Adaptive Traffic Signal Control System Using Object Detection based Approach 4

Adaptive Traffic Signal Control System Using Object Detectio...

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4th international conference on Robotics, Electrical and Signal Processing Techniques, ICREST 2025

作者： Khan, Irfan Hasan, Mehedi Islam, Shamsul Reza, Suman Reza, Tuhin Efaz, Erteza Tawsif Faridpur Engineering College Department of Computer Science & Engineering Faridpur Bangladesh Louisiana State University Division of Electrical & Computer Engineering Baton RougeLA United States

ISBN: (纸本)9798331530938

In Bangladesh, most four-legged intersections use a static-timed or manually-controlled traffic signaling approach, which creates irrefutable congestion and requires human involvement. this paper proposes an adaptive traffic control system utilizing the YOLO object detection framework within CNNs to address this issue. the system captures and frames images using cameras facing every road at a roundabout to detect and count vehicles in real-time for providing lights based on the traffic conditions, prioritizing emergency vehicles such as ambulances, firetrucks, and police-car while also maintaining queues. It sets the signal duration considering road condition. Using a dataset of 10,462 images across 12 classifications of automobiles and a transfer learning approach in YOLOv8, the model achieved a mAP50 score of 0.90. this automated method reasonably enhances traffic flow management by dynamically adjusting signal lights without human intervention. © 2025 ieee.

关键词： Adaptive control systems

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Proceedings - 10th ieee international conference on engineering of Complex computer systems, ICECCS 2005

Proceedings - 10th IEEE International Conference on Engineer...

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10th ieee international conference on engineering of Complex computer systems, ICECCS 2005

the proceedings contain 70 papers from the 10th ieee international conference on engineering of Complex computer systems, ICECCS 2005. the topics discussed include: software engineering approaches to Semantic Web;an introduction to self-healing Web services;a framework for SOFL-based program review;a strategy for component-based modeling and refinement;evaluating conformance of UML models to design patterns;formal requirements-based programming for complex systems;a slice Monad transformer and its applications in program slicing;exploiting OS-level mechanisms to implement mobile code security;and mediation systems modeling and verification.

关键词： Large scale systems

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A Novel Pressure Sensor with Composite Sensitive Film for High Precision Measurement at Broad Range 38

A Novel Pressure Sensor with Composite Sensitive Film for Hi...

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38th ieee international conference on Micro Electro Mechanical systems, MEMS 2025

作者： Chen, Xiaopeng Ling, Sijia Tong, Hanyang Xiao, Yujing Zhang, Jin Yu, Zhengyin Jin, Qinghui Ningbo University The Faculty of Electrical Engineering and Computer Science China Chinese Academy of Sciences Shanghai Institute of Microsystem and Information Technology China

ISBN: (纸本)9798331508890

Microelectromechanical system (MEMS) based pressure sensors have been utilized for decades;however, new trends in pressure sensors have recently emerged, such as increased sensitivity, a broader range and reduced chip size. this paper presents a tiny 0.6mm×0.8mm piezoresistive pressure sensor that offers exceptional sensitivity (0.27mV/kPa/3.3V) at a wide range of pressures (0-1MPa). the innovative composite pressure-sensitive film of the sensor is composed of a 10μm "*"-shaped single-crystalline silicon structure and a remarkably thin thickness of only 2.5μm poly-silicon film. It is developed utilizing the thin-film under bulk-silicon technique. And simultaneous improvement of detection sensitivity and linearity is achieved by etching out the nonlinear deformation region of the film. © 2025 ieee.

关键词： Pressure sensors

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Decoding EEG-based Motor Imagery of Hand Grasp Types for an Amputee Due to Birth Trauma 13

Decoding EEG-based Motor Imagery of Hand Grasp Types for an ...

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13th international Winter conference on Brain-computer Interface, BCI 2025

作者： Ahn, Seong-Ho Kim, Zion Jung, Jun Ha Lee, Hyeon-Jun Kim, Heejin Cho, Jungu Jeong, Jaeseung Dept. Artificial Intelligence The Catholic University of Korea Bucheon Korea Republic of Dept. Mechanical Engineering KAIST Daejeon Korea Republic of Dept. Brain and Cognitive Sciences KAIST Daejeon Korea Republic of Dept. Bio and Brain Engineering KAIST Daejeon Korea Republic of Dept. Industrial Design KAIST Daejeon Korea Republic of AI R&D Division CJ Group Seoul Korea Republic of

ISBN: (纸本)9798331521929

An amputee due to birth trauma represents a very unique case, in which amputation occurred from delivery process itself. Providing appropriate prosthetics is crucial for enabling such case to improve their daily workout and provide entirely new experiences. However, in such case, conventional surface electromyography (sEMG)-based methods for prosthetic control are unsuitable due to the lack of sufficient sEMG signals, as a case has never used the amputated limb since birth. As an alternative to sEMG, we apply an electroencephalography (EEG)-based approach for prosthetic control. In this study, we demonstrated the feasibility of EEG-based motor imagery decoding for hand grasp types to control a prosthetic hand. We collected 10 days of EEG data about one subject and achieved a 10x5-fold cross-validation accuracy of 0.8740 ± 0.0965 in classifying cylindrical and lateral grasps using time delay embedding (TDE) and tangent space mapping (TSM). Our results demonstrate the effectiveness of TSM as an EEG decoder and the performance improvement achieved by TDE. Future work will focus on adapting this approach for real-world brain-computer interface applications. © 2025 ieee.

关键词： Brain computer interface

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Scientific Documents Recommendation based on Graph Convolutional Network

Scientific Documents Recommendation Based on Graph Convolut...

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PhD Symposium, Posters, Demos, and A Web for more inclusive, sustainable and prosperous societies, WEB-for-GOOD 2024 and 1st international workshop on AI and Web Data Analytics, AIWDA 2024 form the 25th international conference on Web Information systems engineering, WISE 2024

作者： Li, Jianmin School of Cyber Security and Computer Hebei University Baoding071002 China Hebei Machine Vision Engineering Research Center Hebei University Baoding071002 China

ISBN: (纸本)9789819614820

the rapid growth in the number of scientific documents makes it increasingly necessary to provide researchers with efficient paper recommendation services. Since scientific documents contain many mathematical expressions and rich text information, effectively mining this information to improve recommendation quality is a challenging and necessary task. therefore, this paper proposes a method that fuses content-based and Graph Convolutional Network (GCN) introducing the multi-head attention mechanism for scientific document recommendation. the method employs Hesitant Fuzzy Set (HFS) and Bidirectional Encoder Representations from Transformers (BERT) to calculate the similarity between mathematical expressions and their context, respectively, and utilizes GCN to learn the complex relationships between nodes and mine the potential similarity between nodes. then, the multi-head attention mechanism is introduced to dynamically assign importance weights to neighbor nodes to enhance the expression of embedding vectors, thereby generating more accurate and personalized recommendation lists. Experimental results show that the method performs well on both Ntcir and extended Chinese datasets, achieving maximum F1_Score vales of 0.817 and 0.837 at Top-50 and Top-30, respectively. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolution

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PDNet: A Novel Approach to Plant Disease Detection using CNN and Keras 6

PDNet: A Novel Approach to Plant Disease Detection using CNN...

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

作者： Jain, Garima Shukla, Amita Chaudhary, Anamika Sharma, Nidhi Bisht, Sovers Singh Jain, Ankush Department of Computer Science and Buisness Systems Noida Institute of Engineering and Technology Greater Noida India Department of Data Science Noida Institute of Engineering and Technology Greater Noida India Department of Data Science Noida Institute of Engineering and Technology Delhi India Department of Computer Science and Engineering Netaji Subhas University of Technology Delhi India

ISBN: (纸本)9798331522667

this research addresses the pressing global demand for food by leveraging cutting-edge deep learning techniques for automating plant disease detection. Focusing on tomato and potato leaf diseases, the study utilized the PlantVillage dataset to compare classical machine learning methods, such as Local Binary Patterns (LBP) combined with classifiers like kNN, SVM, and Extreme Learning Machines, against modern Convolutional Neural Network (CNN) architectures. these included MobileNet, DenseNet201, ResNet50, Inception V3, and VGG16/19. A custom-designed CNN model was developed with unique configurations implemented using Keras and TensorFlow. the model was tested for binary, 6-class, and 10-class classifications, achieving remarkable accuracy rates of 99.6%, 98.4%, and 97.2%, respectively. Notably, after 50 training epochs, the model achieved a peak accuracy of 99.78% for plant disease classification. A practical web-based application was also developed, integrating the best-performing model to facilitate real-time leaf disease detection and notify farmers via email. this approach demonstrates a significant advancement in sustainable agriculture by providing an efficient, accurate, and scalable solution for early disease detection, which is critical for improving crop yield and productivity. © 2025 ieee.

关键词： Convolutional neural networks

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A Distributed Event-Orchestrated Digital Twin Architecture for Optimizing Energy-Intensive Industries

A Distributed Event-Orchestrated Digital Twin Architecture f...

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10th international conference on Internet of things, Big Data and Security, IoTBDS 2025

作者： Bertozzi, Nicolò Geraci, Anna Bergamasco, Letizia Ferrera, Enrico Pristeri, Edoardo Pastrone, Claudio Fondazione Links Via Pier Carlo Boggio 61 Turin10138 Italy Department of Control and Computer Engineering Politecnico di Torino Corso Duca degli Abruzzi 24 Turin10129 Italy

ISBN: (纸本)9789897587504

this paper presents a novel distributed architecture designed to spawn digital twin solutions to improve energy efficiency in energy-intensive industrial scenarios. By executing user-defined workflows, our platform enables the implementation of real-time monitoring, forecasting, and simulation microservices to enhance decision-making strategies for optimizing industrial processes. Leveraging a stateless centralized orchestration mechanism built around an Apache Kafka-based backbone, the platform ensures scalability, fault tolerance, and efficient handling of heterogeneous data. Key features include intuitive workflow configuration, asynchronous communication for streamlined workflow execution, and API-driven scheduling for dynamic, event-based task management. this platform will be deployed and validated in several energy-intensive industrial scenarios, supporting the management of energy systems of different plants, to prove its effectiveness across a wide range of energy management challenges. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Foundries

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