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Single Modality and Joint Fusion for Emotion Recognition on RAVDESS Dataset

SN Computer Science 2024年第6期5卷 669页

作者： Haddad, Syrine Daassi, Olfa Belghith, Safya Laboratory of Robotics Informatics and Complex Systems (RISC Lab-LR16ES07) Tunis Tunisia National Engineering School of Tunis University of Tunis El manar Tunis 1002 Tunisia National Engineering School of Carthage University of Carthage Carthage 2035 Tunisia

Over the last decade, emotion recognition has become a widely researched area worth considering in any project related to affective computing. Due to the limitless applications of this new discipline, the development of emotion recognition systems has emerged as a lucrative opportunity in the corporate sector. Emotion recognition can be detected in many ways, such as face, speech, text, gestures, etc. Hence, this article presents a comprehensive survey of emotion recognition methods, focusing on three key modalities: visual, speech, and audio-visual. Moreover, a novel approach for each modality is proposed, and a comparative analysis is conducted with existing methods to assess their effectiveness. The results of this study revealed that face emotion recognition on the RAVDESS dataset can achieve good results compared to speech emotion recognition, which was the opposite case in previous literature. Combined modalities were found to likely achieve even better results with an accuracy of 89% compared to previous works. Finally, this article concludes by offering new insights and suggestions for future research. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Computational models Face emotion recognition Multi-modal emotion recognition RAVDESS dataset Speech emotion recognition

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Semi-analytical finite element method applied for characterizing micropolar fibrous composites

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Applied Mathematics and Mechanics(English Edition) 2024年第12期45卷 2147-2164页

作者： J.A.OTERO Y.ESPINOSA-ALMEYDA R.RODRIGUEZ-RAMOS J.MERODIO School of Engineering and Sciences Monterrey Institute of TechnologyEstado de Mexico 52926Mexico Institute of Engineering and Technology Autonomous University of Ciudad JuarezCiudad JuarezChihuahua 32310Mexico Postgraduate Program in Computational Modeling in Science and Technology Federal Fluminense UniversityRıo de Janeiro 27255-125Brazil Faculty of Mathematics and Computer Science University of HavanaLa Habana 10400Cuba Department of Mathematics Applied to ICT School of Informatics Systems EngineeringTechnical University of MadridMadrid 28031Spain

A semi-analytical finite element method(SAFEM),based on the two-scale asymptotic homogenization method(AHM)and the finite element method(FEM),is implemented to obtain the effective properties of two-phase fiber-reinforced composites(FRCs).The fibers are periodically distributed and unidirectionally aligned in a homogeneous *** framework addresses the static linear elastic micropolar problem through partial differential equations,subject to boundary conditions and perfect interface contact *** mathematical formulation of the local problems and the effective coefficients are presented by the *** local problems obtained from the AHM are solved by the FEM,which is denoted as the *** numerical results are provided,and the accuracy of the solutions is analyzed,indicating that the formulas and results obtained with the SAFEM may serve as the reference points for validating the outcomes of experimental and numerical computations.

关键词： semi-analytical approach fiber-reinforced composite(FRC) effective property finite element method(FEM) asymptotic homogenization method(AHM) micropolar elasticity

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Enabling data-driven anomaly detection by design in cyber-physical production systems

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Cybersecurity 2022年第3期5卷 34-51页

作者： Rui Pinto Gil Goncalves Jerker Delsing Eduardo Tovar Department of Informatics Engineering Faculty of EngineeringUniversity of PortoPortoPortugal EISLAB Lulea University of TechnologyLuleaSweden Research Centre in Real-Time and Embedded Computing Systems Polytechnic of Porto-School of EngineeringPortoPortugal

Designing and developing distributed cyber-physical production systems(CPPS)is a time-consuming,complex,and error-prone *** systems are typically heterogeneous,i.e.,they consist of multiple components implemented with different languages and development *** of the main problems nowadays in CPPS implementation is enabling security mechanisms by design while reducing the complexity and increasing the system’s *** the IEC 61499 standard is an excellent approach to tackle these challenges by enabling the design,deployment,and management of CPPS in a model-based engineering *** propose a method for CPPS design based on the IEC 61499 *** method allows designers to embed a bio-inspired anomaly-based host intrusion detection system(A-HIDS)in Edge *** A-HIDS is based on the incremental Dendritic Cell Algorithm(iDCA)and can analyze OPC UA network data exchanged between the Edge devices and detect attacks that target the CPPS’Edge *** study’s findings have practical implications on the industrial security community by making novel contributions to the intrusion detection problem in CPPS considering immune-inspired solutions,and cost-effective security by design system *** to the experimental data,the proposed solution can dramatically reduce design and code complexity while improving application maintainability and successfully detecting network attacks without negatively impacting the performance of the CPPS Edge devices.

关键词： Artificial immune systems Cyber-physical production systems IEC 61499 Function blocks Industrial Internet of Things Anomaly-based host intrusion detection system Model-based engineering

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Coevolution of Myoelectric Hand Control under the Tactile Interaction among Fingers and Objects

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Cyborg and Bionic systems 2022年第1期2022卷 285-302页

作者： Yuki Kuroda Yusuke Yamanoi Shunta Togo Yinlai Jiang Hiroshi Yokoi Joint Doctoral Program for Sustainability Research Graduate School of Informatics and Engineering The University of Electro-CommunicationsTokyoJapan Department of Mechan ical and Intelligent System Engineering Graduate School of Informatics and Engineering The University of Electro Communications TokyoJapan Center for Neuroscience and Biomedical Engineering The University of Electro Communications TokyoJapan Bejing Innovation Center for Inelligent Robots and Systems BeijingChina

The usability of a prosthetic hand difers significantly from that of a real ***,the complexity of manipulation increases as the number of degrees of freedom to be controlled increases,making manipulation with biological signals extremely *** overcome this problem,users need to select a grasping posture that is adaptive to the object and a stable grasping method that prevents the object from *** previous studies,these have been left to the operating skills of the user,which is extremely difficult to *** this study,we demonstrate how stable and adaptive grasping can be achieved according to the object regardless of the user's operation *** required grasping technique is achieved by determining the correlation bet ween the motor output and each sensor through the interaction between the prosthetic hand and the surrounding stimuli,such as myoelectricity,sense of touch,and grasping *** agents of the 16 DOF robot hand were trained with the myoelectric signals of six participants,including one child with a congenital forearm ***,each agent could open and close the hand in response to the myoeletric stimuli and could accomplish the object pickup *** the tasks,the agents successfully identified grasping patterns suitable for practical and stable positioning of the *** addition,the agents were able to pick up the object in a similar posture regardless of the partiipant,suggesting that the hand was optimized by evolutionary computation to a posture that prevents the object from being dropped.

关键词： robot Objects overcome

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Detecting Model Poisoning Attacks Via Dummy Symbol Insertion for Secure Over-the-Air Federated Learning 22

Detecting Model Poisoning Attacks Via Dummy Symbol Insertion...

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22nd IEEE Consumer Communications and Networking Conference, CCNC 2025

作者： Zhou, Hang Chiang, Yi-Han Chen, Caijuan Wang, Xiaoyan Ji, Yusheng National Institute of Informatics Information Systems Architecture Science Research Division Tokyo Japan Osaka Metropolitan University Department of Electrical and Electronic Systems Engineering Osaka Japan Graduate School of Science and Engineering Ibaraki University Hitachi Japan

ISBN: (纸本)9798331508050

With the rapid advancement of intelligent IoT services, the need for high-quality and efficient wireless communication has become increasingly critical for information exchanges and collaborations among intelligent edge devices such as autonomous mobile robots (AMRs), robots in smart factories, and surveillance cameras, etc., Federated Learning (FL) is a promising distributed learning framework by exploring the computation capability on edge devices while protecting data privacy of users. On the other hand, Over-the-Air (OTA) computation techniques is a new paradigm of integrated computation and communication. OTA based FL (OTA-FL) can enhance spectrum efficiency by leveraging the superposition properties of wireless channels for model aggregations. The implementation of OTA-FL on edge devices can further protect user data privacy for clients, improve the throughput of inter-device communications, and enhance the distributed learning performance. However, despite these advantages, the convergence of OTA-FL systems remain vulnerable to model poisoning attacks, presenting significant challenges. In this study, we address these vulnerabilities by proposing a two-phase detection mechanism that secures OTA-FL system while preserving high spectral efficiency. Our simulation results demonstrate that under varying conditions, our approach can make distributed learning more secure and communication-efficient. © 2025 IEEE.

关键词： Secure communication

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Physical Layer Security in AmBC-NOMA Networks with Random Eavesdroppers

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IEEE Internet of Things Journal 2025年第12期12卷 18628-18642页

作者： Pei, Xinyue Wang, Xingwei Huang, Min Chen, Yingyang Li, Xiaofan Tsiftsis, Theodoros A. Northeastern University School of Computer Science and Engineering Shenyang110819 China Northeastern University College of Information Science and Engineering Shenyang110819 China Jinan University College of Information Science and Technology Guangzhou510632 China Jinan University School of Intelligent Systems Science and Engineering Zhuhai519070 China University of Thessaly Department of Informatics Telecommunications Lamia35100 Greece University of Nottingham Ningbo China Department of Electrical and Electronic Engineering Ningbo315100 China

In this work, we investigate the physical layer security (PLS) of ambient backscatter communication non-orthogonal multiple access (AmBC-NOMA) networks where non-colluding eavesdroppers (Eves) are randomly distributed. In the proposed system, a base station (BS) transmits a superimposed signal to a typical NOMA user pair, while a backscatter device (BD) simultaneously transmits its unique signal by reflecting and modulating the BS’s signal. Meanwhile, Eves passively attempt to wiretap the ongoing transmissions. Notably, the number and locations of Eves are unknown, posing a substantial security threat to the system. To address this challenge, the BS injects artificial noise (AN) to mislead the Eves, and a protected zone is employed to create an Eve-exclusion area around the BS. Theoretical expressions for outage probability (OP) and intercept probability (IP) are provided to evaluate the system’s reliability-security trade-off. Asymptotic behavior at high signal-to-noise ratio (SNR) is further explored, including the derivation of diversity orders for the OP. Numerical results validate the analytical findings through extensive simulations, demonstrating that both the AN injection and protected zone can effectively enhance PLS. Furthermore, analysis and insights of different key parameters, including transmit SNR, reflection efficiency at the BD, power allocation coefficient, power fraction allocated to desired signal, Eve-exclusion area radius, Eve distribution density, and backscattered AN cancellation efficiency, on OP and IP are also provided. © 2014 IEEE.

关键词： Signal to noise ratio

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Droplet 3D cryobioprinting for fabrication of free-standing and volumetric structures

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Aggregate 2024年第5期5卷 433-444页

作者： Joshua Weygant Ali Entezari Fritz Koch Ricardo AndréGalaviz Carlos Ezio Garciamendez Pável Hernández Vanessa Ortiz David Sebastián Rendon Ruiz Francisco Aguilar Andrea Andolﬁ Ling Cai Sushila Maharjan Anayancy Osorio Yu Shrike Zhang Division of Engineering in Medicine Department of MedicineBrigham and Women’s HospitalHarvard Medical SchoolCambridgeMassachusettsUSA School of Biomedical Engineering University of Technology SydneyBroadwayNew South WalesAustralia Laboratory for Bioinspired Materials for Biomedical Engineering IMTEK—Department of Microsystems EngineeringUniversity of FreiburgFreiburgGermany Department of Informatics BioengineeringRobotics and Systems Engineering(DIBRIS)University of GenovaGenovaItaly Department of Engineering University of CambridgeCB21PZ CambridgeUK

Droplet-based bioprinting has shown remarkable potential in tissue engineering and regenerative ***,it requires bioinks with low viscosities,which makes it challenging to create complex 3D structures and spatially pattern them with different *** study introduces a novel approach to bioprinting sophisti-cated volumetric objects by merging droplet-based bioprinting and cryobioprinting *** leveraging the beneﬁts of cryopreservation,we fabricated,for theﬁrst time,intricate,self-supporting cell-free or cell-laden structures with single or multiple materials in a simple droplet-based bioprinting process that is facilitated by depositing the droplets onto a cryoplate followed by crosslinking during *** feasibility of this approach is demonstrated by bioprinting several cell types,with cell viability increasing to 80%–90%after up to 2 or 3 weeks of ***,the applicational capabilities of this approach are showcased by bio-printing an endothelialized breast cancer *** results indicate that merging droplet and cryogenic bioprinting complements current droplet-based bioprinting techniques and opens new avenues for the fabrication of volumetric objects with enhanced complexity and functionality,presenting exciting potential for biomedical applications.

关键词： 3D bioprinting biofabrication cryogenic bioprinting droplet printing inkjet tissue engineering

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Evaluation Methods and Measures for Causal Learning Algorithms

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2022年第6期3卷 924-943页

作者： Cheng, Lu Guo, Ruocheng Moraffah, Raha Sheth, Paras Candan, K. Selcuk Liu, Huan Arizona State University School Of Computing Informatics And Decision Systems Engineering TempeAZ85287 United States City University Of Hong Kong School Of Data Science Hong Kong

The convenient access to copious multifaceted data has encouraged machine learning researchers to reconsider correlation-based learning and embrace the opportunity of causality-based learning, i.e., causal machine learning (causal learning). Recent years have, therefore, witnessed great effort in developing causal learning algorithms aiming to help artificial intelligence (AI) achieve human-level intelligence. Due to the lack of ground-truth data, one of the biggest challenges in current causal learning research is algorithm evaluations. This largely impedes the cross-pollination of AI and causal inference and hinders the two fields to benefit from the advances of the other. To bridge from conventional causal inference (i.e., based on statistical methods) to causal learning with Big Data (i.e., the intersection of causal inference and machine learning), in this survey, we review commonly used datasets, evaluation methods, and measures for causal learning using an evaluation pipeline similar to conventional machine learning. We focus on the two fundamental causal inference tasks and causality-aware machine learning tasks. Limitations of current evaluation procedures are also discussed. We, then, examine popular causal inference tools/packages and conclude with primary challenges and opportunities for benchmarking causal learning algorithms in the era of Big Data. The survey seeks to bring to the forefront the urgency of developing publicly available benchmarks and consensus-building standards for causal learning evaluation with observational data. In doing so, we hope to broaden the discussions and facilitate collaboration to advance the innovation and application of causal learning. © 2020 IEEE.

关键词： Maximum likelihood estimation

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DeepDect: A Facial Deepfake Video Detection Application using Ensemble Learning 12

DeepDect: A Facial Deepfake Video Detection Application usin...

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12th IEEE Conference on systems, Process and Control, ICSPC 2024

作者： Tay, Wan Xin Chua, Hui Na Jasser, Muhammed Basheer Issa, Bayan Wong, Richard T.K. Sunway University No. 5 Jalan Universiti School of Engineering and Technology Department of Computing and Information Systems Selangor Darul Ehsan Bandar Sunway47500 Malaysia University of Aleppo Faculty of Informatics Engineering Syria

ISBN: (纸本)9798350391398

The emerging technology of deepfake video poses significant threats to information integrity and public trust. Deepfake videos come in various forms, including face swaps, lip-syncing, and full-body simulations. Detection algorithms may struggle to generalize across these different types of deepfakes, leading to lower effectiveness in real-world applications. An advanced deepfake detection system is developed using an ensemble approach, combining the strengths of three pre-trained Convolutional Neural Networks (CNNs)ResNeXt50, Xception, and EfficientNet-v2-with Long ShortTerm Memory (LSTM) layers to capture both spatial and temporal features from videos to improve detection accuracy. The ensemble model is further enhanced by incorporating additional features such as lip movements, eye blinks, head poses, and color contrasts to identify subtle inconsistencies in deepfake videos that are often ignored by traditional detection methods. The ensemble model achieves an accuracy of 84.06%, with a good balance between precision and recall, indicating its effectiveness in real-world applications. We developed DeepDect, a web application embedded with the ensemble model, to provide a user-friendly interface for deepfake detection by uploading videos or submitting URL links. The application includes educational content about deepfake techniques to raise user awareness about the potential dangers of deepfakes. © 2024 IEEE.

关键词： Convolutional neural networks

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CASKA-CRT: Chinese Remainder Theorem Empowered Certificateless Aggregate Signcryption Scheme with Key Agreement in IoVs

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-16页

作者： Hou, Yingzhe Cao, Yue Xiong, Hu Sun, Zhili Mumtaz, Shahid Tian, Daxin School of Cyber Science and Engineering Wuhan University Wuhan China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Institute of Communication Systems University of Surrey Guildford U.K Department of Applied Informatics Silesian University of Technology Akademicka Gliwice Poland State Key Laboratory of Vehicle-Infrastructure Integrated ITS the State Key Laboratory of Intelligent Transportation System and the School of Transportation Science and Engineering Beihang University Beijing China

To enhance the privacy of messages in Internet of Vehicles (IoVs), it is critical to preserve the communication security between Road Side Unit (RSU) and numerous vehicles. The primitive of signcryption is introduced to guarantee the confidentiality, integrity and unforgeability of transmitted messages. Nevertheless, the existing signcryption schemes fail to achieve a balance between security and efficiency. In this paper, we construct a Chinese remainder theorem (CRT) empowered certificateless aggregate signcryption scheme with key agreement (CASKA-CRT). As the vehicle joins and leaves dynamically, the proposed scheme can ensure the dynamic security via one modulo division operation. Besides, the certificateless aggregate signcryption and key agreement mechanisms are embedded. The former idea can both address the certificate management and key escrow problems, while the latter technology can create authentication as a premise of secure communication. Based on this construction, the hash-to-group operation and bilinear pairing are avoided, to realize a faster verification with the increased number of messages. Moreover, the security of proposed scheme is proved under the random oracle model. Finally, the performance analysis demonstrates the advantage of CASKA-CRT in terms of security and reliability over related works. IEEE

关键词： Public key cryptography

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