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An improved end-to-end micro-expression recognition system for real-world videos via dual-input CNN architecture

Expert Systems with Applications 2025年 286卷

作者： Gan, Y.S. Liu, Kun-Hong Wu, Min-Huan Liong, Gen-Bing Liong, Sze-Teng School of Architecture Feng Chia University Taichung40724 Taiwan Department of Digital Media Technology School of Film Xiamen University Xiamen China Bachelor of Science in Senior Wellness and Sport Science Tunghai University Taiwan Faculty of Computer Science & Information Technology University of Malaya Kuala Lumpur50603 Malaysia Department of Electronic Engineering Feng Chia University Taichung40724 Taiwan

Micro-expression (ME) recognition reveals nonverbal emotions through subtle, involuntary facial muscle movements. However, the development and commercialization of ME recognition systems have been hindered by the lack of databases that accurately reflect real-world conditions. This study addresses this challenge by proposing a robust end-to-end system designed to operate effectively in unconstrained environments. Existing methods typically rely on a single apex frame, which may be unreliable due to noise, occlusions, or lighting variations. To address these issues, a 3D facial reconstruction technique is applied as a pre-processing step to normalize pose and lighting. A novel dual-peak frame detection strategy is then introduced to extract two expressive optical flow frames, reducing the impact of noise from any single frame. Finally, a Shallow and Small-size Dual-input (SSD) CNN architecture is designed to jointly process the two frames for improved emotion classification. The proposed system achieves strong performance on the challenging in-the-wild MEVIEW dataset, with accuracy and F1-score of 75 % and 77.68 %, respectively. Comprehensive evaluations further validate the effectiveness of the pipeline, highlighting its potential for real-world ME recognition applications. © 2025 Elsevier Ltd

关键词： Optical character recognition

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Using Mobile Sinks in WSN: Computational Complexity and a Theoretical Bound

引用

Chinese Journal of Electronics 2023年第1期20卷 147-150页

作者： Yu Gu Yusheng Ji Hongyang Chen Baohua Zhao Department of Computer Science University of Science and Technology of China Hefei China State Key Laboratory of Networking and Switching Technology Beijing China Information Systems Architecture Science Research Division NII Tokyo Japan Institute of Industrial Science University of Tokyo Tokyo Japan

In this paper, we study the lifetime optimization problem in wireless sensor networks using mobile sink nodes. This problem is inherently difficult since we need to consider both sink scheduling and data routing. Through a simple case study we develop a novel notation named the Placement pattern (PP) to bound traffic patterns with candidate locations. This significantly decreases the number of elements needed to be scheduled. Based on the PP, we mathematically formulate this optimization problem as a Mixed-integer non-linear programming (MINLP), which is very tough and time consuming to solve. By proving that the problem is NP-complete, we point out that instead of seeking an optimal algorithm, heuristic algorithms, especially those with performance guarantee, would be much more desirable to develop. Furthermore, in order to help identify performance gains of heuristic algorithms proposed in the future, we develop a Linear programming (LP) formulation which serves as an upper bound by adopting a reformulation and relaxation technique.

关键词： Wireless sensor networks Upper bound Heuristic algorithms Traffic control Programming Performance gain Routing

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Effect of Artificial Roughness on Heat Transfer and Friction Factor in a Solar Air Heater: A Review 2nd

Effect of Artificial Roughness on Heat Transfer and Friction...

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2nd International Conference on Advances in Materials and Manufacturing technology, ICAMMT 2022

作者： Yadav, Anil Singh Alam, Tabish Saxena, Rajiv Yadav, Raj Kumar Kumar, Rajan Sharma, Abhishek Agrawal, Yogesh Viswanath Allamraju, K. Vyas, Monika Singh, Manmohan Chakroborty, Subhendu Mechanical Engineering Department IES College of Technology MP Bhopal462044 India Architecture Planning and Energy Efficiency CSIR-Central Building Research Institute Uttarakhand Roorkee247667 India Infinity Management and Engineering College MP Sagar470001 India Mechanical Engineering Department Adina Institute of Science and Technology MP Sagar470002 India Department of Mechanical Engineering BIT Sindri Jharkhand Dhanbad828123 India Mechanical Engineering Department Sagar Institute of Research and Technology MP Bhopal462041 India Mechanical Engineering Department Institute of Aeronautical Engineering Telangana Hyderabad500043 India Civil Engineering Department IES College of Technology MP Bhopal462044 India Computer Science and Engineering Department IES College of Technology MP Bhopal462044 India Department of Basic Sciences IITM IES University MP Bhopal462044 India

ISBN: (纸本)9789819929207

In order to convert solar energy into thermal energy, solar air heater (SAH) is commonly used. These are used to convert the solar radiation into heat of working fluid. The effect of various geometric constraints on the friction characteristics and heat transfer (HT) of a SAH has been studied. The paper aims to introduce the various parameters that are involved in the analysis of HT enhancement of SAH. There are various techniques that are involved in the analysis of HT enhancement of SAH. One of these is the use of a passive method, which involves the use of turbulators, ribs or fins on the surface. SAHs that are roughened can improve their HT properties compared to their plain counterparts. This is because the various surface patterns and shapes used in their design can help improve their performance. There have been many different sorts of studies conducted on the many facets of these HT augmentation approaches. Studies showed that combining the roughening process with a rough absorber plate can improve the performance of SAH duct. The goal of this study is to identify the most appropriate roughness component for solar air duct that can meet the different operating conditions. The findings of this study can be used to design and construct enhanced SAH duct system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Flow of fluids

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GöwFed - A novel Federated Network Intrusion Detection System

arXiv

引用

arXiv 2022年

作者： Belenguer, Aitor Pascual, Jose A. Navaridas, Javier Department of Computer Architecture and Technology University of the Basque Country UPV/EHU Manuel Lardizabal 1 Donostia-San Sebastian20018 Spain

Network intrusion detection systems are evolving into intelligent systems that perform data analysis while searching for anomalies in their environment. Indeed, the development of deep learning techniques paved the way to build more complex and effective threat detection models. However, training those models may be computationally infeasible in most Edge or IoT devices. Current approaches rely on powerful centralized servers that receive data from all their parties - violating basic privacy constraints and substantially affecting response times and operational costs due to the huge communication overheads. To mitigate these issues, Federated Learning emerged as a promising approach, where different agents collaboratively train a shared model, without exposing training data to others or requiring a compute-intensive centralized infrastructure. This work presents GöwFed, a novel network threat detection system that combines the usage of Gower Dissimilarity matrices and Federated averaging. Different approaches of GöwFed have been developed based on state-of the-art knowledge: (1) a vanilla version;and (2) a version instrumented with an attention mechanism. Furthermore, each variant has been tested using simulation oriented tools provided by TensorFlow Federated framework. In the same way, a centralized analogous development of the Federated systems is carried out to explore their differences in terms of scalability and performance - across a set of designed experiments/scenarios. Overall, GöwFed intends to be the first stepping stone towards the combined usage of Federated Learning and Gower Dissimilarity matrices to detect network threats in industrial-level networks. © 2022, CC BY-NC-SA.

关键词： Internet of things

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A Lightweight Convolutional Neural Network with Representation Self-challenge for Fingerprint Liveness Detection

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computers, Materials & Continua 2022年第10期73卷 719-733页

作者： Jie Chen Chengsheng Yuan Chen Cui Zhihua Xia Xingming Sun Thangarajah Akilan School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Key Laboratory of Public Security Information Application Based on Big-Data Architecture Ministry of Public SecurityZhejiang Police CollegeHangzhou310053China Jiangsu Yuchi Blockchain Research Institute Nanjing210044China Department of Software Engineering Lakehead UniversityThunder BayON P7B 5E1Canada

Fingerprint identification systems have been widely deployed in many occasions of our daily ***,together with many advantages,they are still vulnerable to the presentation attack(PA)by some counterfeit *** address challenges from PA,fingerprint liveness detection(FLD)technology has been proposed and gradually attracted people’s *** vast majority of the FLD methods directly employ convolutional neural network(CNN),and rarely pay attention to the problem of overparameterization and over-fitting of models,resulting in large calculation force of model deployment and poor model *** at filling this gap,this paper designs a lightweight multi-scale convolutional neural network method,and further proposes a novel hybrid spatial pyramid pooling block to extract abundant features,so that the number of model parameters is greatly reduced,and support multi-scale true/fake fingerprint ***,the representation self-challenge(RSC)method is used to train the model,and the attention mechanism is also adopted for optimization during execution,which alleviates the problem of model over-fitting and enhances generalization of detection ***,experimental results on two publicly benchmarks:LivDet2011 and LivDet2013 sets,show that our method achieves outstanding detection results for blind materials and *** size of the model parameters is only 548 KB,and the average detection error of cross-sensors and cross-materials are 15.22 and 1 respectively,reaching the highest level currently available.

关键词： FLD lightweight multi-scale RSC blind materials

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Göwfeda Novel Federated Network Intrusion Detection System

SSRN

引用

SSRN 2022年

Network intrusion detection systems are evolving into intelligent systems that perform data analysiswhile searching for anomalies in their environment. Indeed, the development of deep learningtechniques paved the way to build more complex and effective threat detection models. However,training those models may be computationally infeasible in most Edge or IoT devices. Currentapproaches rely on powerful centralized servers that receive data from all their parties – violatingbasic privacy constraints and substantially affecting response times and operational costs due to thehuge communication overheads. To mitigate these issues, Federated Learning emerged as a promisingapproach, where different agents collaboratively train a shared model, without exposing training datato others or requiring a compute-intensive centralized infrastructure. This work presents GöwFed,a novel network threat detection system that combines the usage of Gower Dissimilarity matricesand Federated averaging. Different approaches of GöwFed have been developed based on state-ofthe-art knowledge: (1) a vanilla version;and (2) a version instrumented with an attention ***, each variant has been tested using simulation oriented tools provided by TensorFlowFederated framework. In the same way, a centralized analogous development of the Federated systemsis carried out to explore their differences in terms of scalability and performance – across a set ofdesigned experiments/scenarios. Overall, GöwFed intends to be the first stepping stone towards thecombined usage of Federated Learning and Gower Dissimilarity matrices to detect network threats inindustrial-level networks. © 2022, The Authors. All rights reserved.

关键词： Internet of things

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From Detection to Traversal: a Probabilistic Framework for UAS-Assisted Landmine Mapping and Circumvention

From Detection to Traversal: a Probabilistic Framework for U...

引用

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： J. Josiah Steckenrider Dongbin Kim Pratheek Manjunath Jack Simpson Charles Rosbrook Micah Weiss Department of Civil and Mechanical Engineering United States Military Academy West Point NY USA College of Engineering Technology and Architecture University of Hartford West Hartford CT USA Department of Electrical Engineering and Computer Science United States Military Academy West Point NY USA

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

This research presents a robust probabilistic framework for minefield localization, mapping, and avoidance, addressing a technological gap in the field of aerial countermine intelligence, while bypassing the well-established techniques of landmine detection. Our approach propagates the pose uncertainty matrix delivered by a drone's flight controller's Kalman filter to probabilistically estimate the location of detected mines. This probability map then seeds an artificial potential field path generator which creates a safe path for ground traversal by producing waypoints through the minefield. The system's performance is evaluated in simulations and validated through flight trials, demonstrating its potential to improve the efficiency and safety of UAV-assisted minefield navigation and threat avoidance.

关键词： Location awareness Landmine detection Uncertainty System performance Atmospheric modeling Probabilistic logic Aircraft navigation Generators Safety Kalman filters

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Advancements in 5G and 6G Technologies Shaping the Future of Global Connectivity and Communication

Advancements in 5G and 6G Technologies Shaping the Future of...

引用

Sustainable Communication Networks and Application (ICSCNA), International Conference on

作者： Sunita Pachar Satti Sudha Mohan Reddy Gouthami Kompally Lakshmi Narasimhan Srinivasagopalan Rohidas Balu Sangore Sivakoteswararao Katta IBM Department GLA University Department of ECE SRKR Engineering College India Department of CSE-IOT Malla Reddy Egineering College(A) India Software Development Enterprise Architecture Plano TX USA Computer Science and Engineering MIT Art Design Technology University Department of Mechanical KIETW Kakinada

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530020

The evolution of wireless communication is poised for a major shift with the transition from 5G to 6G, a leap characterized by breakthroughs in speed, ultra-reliable low-latency communication, and AI-driven network optimization. This paper examines these advancements, focusing on sub-millisecond latency, terahertz spectrum utilization, and enhanced network capabilities tailored to industries such as smart infrastructure, healthcare, and autonomous vehicles. While 6G promises revolutionary improvements, it also presents new challenges, including increased computational complexity and energy demands, data privacy concerns, and efficient spectrum allocation. The proposed model aims to address these issues by integrating AI and machine learning for optimized resource management, resulting in a high-performance, cost-effective solution for real-time, data-intensive applications. To assess the model's effectiveness, comprehensive simulations and real-world trials will be conducted, measuring critical metrics such as network throughput, latency, reliability, and energy efficiency. This study offers an all-encompassing guide to understanding and harnessing the transformative potential of 6G technology, laying the groundwork for future wireless communication systems.

关键词： 6G mobile communication Ethics Technological innovation Computational modeling Medical services Energy efficiency Real-time systems Security Resource management Standards

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An Identity-Based Encryption Method for SDN-Enabled Source Routing Systems

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Security and Communication Networks 2022年第0期2022卷

作者： Alzahrani, Bander Chaudhry, Shehzad Ashraf College of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Department of Computer Engineering Faculty of Engineering and Architecture Istanbul Gelisim University Istanbul Turkey

In this study, we consider endpoints communicating over a software-defined networking (SDN)-based architecture using source routing, i.e., packets are routed through a path selected by the packet sender, and we provide a security solution that enforces the selected path. In particular, our solution allows a sender to select the path that a packet should go through using a constant-size cryptographic construction which is referred to as the authenticator. A recipient can examine an authenticator and verify that the received packet has followed the path selected by the sender. Additionally, any intermediate "programmable"switch can verify whether or not it is included in the path of a packet. Our solution can be used even for paths that include multiple recipients (e.g., multicast paths), as well as multiple parallel paths (e.g., multipath transmissions). We implement our solution by leveraging identity-based encryption (IBE), so it can be used by any sender that knows the identifiers of the links that compose the desired path, i.e., information that the sender usually already knows as part of the source routing protocol. Our solution is realistic since it can be implemented over a variety of platforms with tolerable overhead. © 2022 Bander Alzahrani and Shehzad Ashraf Chaudhry.

关键词： Cryptography

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Improvement of Color Image Analysis Using a New Hybrid Face Recognition Algorithm based on Discrete Wavelets and Chebyshev Polynomials

arXiv

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arXiv 2023年

作者： Muhialdeen, Hassan M. Abdulrahman, Asma A. Eleiwy, Jabbar Abed Tahir, Fouad S. Khlaponin, Yurii Al-Sharify, Mushtaq Talib Department of Computer Engineering Aliraqia University 22 Sabaabkar Adamia Baghdad Iraq Department of Applied Sciences University of Technology 52 Alsena street Baghdad Iraq Department of Cybersecurity and Computer Engineering Kyiv National University of Construction and Architecture 31 Povitroflotskyi ave Kyiv03037 Ukraine Department of Communication Technical Engineering Al-Farahidi University Baghdad Iraq

This work is unique in the use of discrete wavelets that were built from or derived from Chebyshev polynomials of the second and third kind, filter the Discrete Second Chebyshev Wavelets Transform (DSCWT), and derive two effective filters. The Filter Discrete Third Chebyshev Wavelets Transform (FDTCWT) is used in the process of analyzing color images and removing noise and impurities that accompany the image, as well as because of the large amount of data that makes up the image as it is taken. These data are massive, making it difficult to deal with each other during transmission. However to address this issue, the image compression technique is used, with the image not losing information due to the readings that were obtained, and the results were satisfactory. Mean Square Error (MSE), Peak Signal Noise Ratio (PSNR), Bit Per Pixel (BPP), and Compression Ratio (CR) Coronavirus is the initial treatment, while the processing stage is done with network training for Convolutional Neural Networks (CNN) with Discrete Second Chebeshev Wavelets Convolutional Neural Network (DSCWCNN) and Discrete Third Chebeshev Wavelets Convolutional Neural Network (DTCWCNN) to create an efficient algorithm for face recognition, and the best results were achieved in accuracy and in the least amount of time. Two samples of color images that were made or implemented were used. The proposed theory was obtained with fast and good results;the results are evident shown in the tables below. © 2023, CC BY.

关键词： Wavelet transforms

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