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2024 IEEE International Conference on Automation and Computation, AUTOCOM 2024

作者： Ravichandran, M. Laxmikant, Kumar Muthu, Annamalai Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai India University of Technology & Applied Science Department of Electrical and Electronics Engineering Nizwa Oman

ISBN: (纸本)9798350382723

As cities grow, handling traffic in big urban are-as becomes a huge proble-m. More cars on the road and not enough roads le-ad to heavy traffic jams. This increases trave-l time and harms our environment. Our study tackle-s these problems with a ne-w approach. We use real-time- lane detection with YOLOv8 and adaptable- traffic lights. Using sharp computer vision, our system pinpoints vehicle-s. It adjusts traffic light timings on-the-go to improve traffic flow. Our model works e-xtremely accurately. During the- learning phase, it achieve-d a mAP50 score of 99.3% and a mAP50-95 score of 87.4%. In the te-sting phase, it got a mAP score of 99.2% and a mAP50-95 score of 86.2%. The re-sults highlight how the system can improve city trave-l. It's valuable for city planners and traffic officials. It helps the-m understand smart transportation systems bette-r. © 2024 IEEE.

关键词： computer vision

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Memory-Augmented Deep Deterministic Policy Gradient 16th

Memory-Augmented Deep Deterministic Policy Gradient

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16th International Conference on Social robotics, ICSR + BioMed 2024

作者： Qiu, Qian Zeng, Fanyu Yang, Haigen Xing, Guanyu Ge, Shuzhi Sam School of Communication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China College of Computer Science Sichuan University Chengdu China Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

ISBN: (纸本)9789819789627

With the advancement of intelligent technologies, particularly deep reinforcement learning, Unmanned Aerial Vehicles (UAVs) are being widely deployed across various scenarios. However, current remote-controlled UAV methods and existing intelligent decision-making algorithms struggle to effectively respond to dynamic and partially observable situations. To tackle this issue, we propose the Memory-augmented Deep Deterministic Policy Gradient (MemDDPG) algorithm. The MemDDPG algorithm leverages a Long Short-Term Memory (LSTM) network to use past state information for current decision-making, enabling UAVs to perform accurately in dynamic scenarios. By incorporating memory-based mechanisms, MemDDPG addresses the limitations of conventional methods, enhancing UAVs’ ability to manage complex environments. This algorithm improves decision-making and ensures UAVs operate more autonomously and efficiently in unpredictable situations. Experiments demonstrate the effectiveness and feasibility of the MemDDPG algorithm in enhancing the intelligent decision-making capabilities of UAVs, showing significant improvements in adaptability and decision-making accuracy in dynamic situations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep reinforcement learning

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Near-Field Communications: A Comprehensive Survey

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IEEE Communications Surveys and Tutorials 2024年第3期27卷 1687-1728页

作者： Liu, Yuanwei Ouyang, Chongjun Wang, Zhaolin Xu, Jiaqi Mu, Xidong Swindlehurst, A. Lee School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of University College Dublin School of Electrical and Electronic Engineering College of Engineering and Architecture DublinD04 V1W8 Ireland Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom University of California Department of Electrical Engineering and Computer Science IrvineCA92697 United States BelfastBT3 9DT United Kingdom

Multiple-antenna technologies are evolving towards larger aperture sizes, extremely high frequencies, and innovative antenna types. This evolution is fostering the emergence of near-field communications (NFC) in future wireless systems. Considerable attention has been directed towards this cutting-edge technology due to its potential to enhance the capacity of wireless networks by introducing increased spatial degrees of freedom (DoFs) in the range domain. Within this context, a comprehensive review of the state of the art on NFC is presented, with a specific focus on its 1) fundamental operating principles, 2) channel modeling, 3) performance analysis, 4) signal processing techniques, and 5) integration with other emerging applications. Specifically, 1) the basic principles of NFC are characterized from both physics and communications perspectives, unveiling its unique properties in contrast to far-field communications. 2) Building on these principles, deterministic and stochastic near-field channel models are explored for spatially-discrete (SPD) and continuous-aperture (CAP) arrays. 3) Based on these models, existing contributions to near-field performance analysis are reviewed in terms of DoFs/effective DoFs (EDoFs), the power scaling law, and transmission rate. 4) Existing signal processing techniques for NFC are systematically surveyed, which include channel estimation, beamforming design, and low-complexity beam training. 5) Major issues and research opportunities in incorporating near-field models into other promising technologies are identified to advance NFC's deployment in next-generation networks. Throughout this paper, promising directions are highlighted to inspire future research endeavors in the realm of NFC, underscoring its significance in the advancement of wireless communication technologies. © 1998-2012 IEEE.

关键词： Near field communication

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Differential Impacts of Monologue and Conversation on Speech Emotion Recognition

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IEEE Transactions on Affective Computing 2024年第2期16卷 485-498页

作者： Chien, Woan-Shiuan Upadhyay, Shreya G. Lin, Wei-Cheng Busso, Carlos Lee, Chi-Chun National Tsing Hua University Department of Electrical Engineering Taiwan The University of Texas at Dallas Erik Jonsson School of Engineering & Commputer Science RichardsonTX United States Carnegie Mellon University Language Technologies Institute School of Computer Science PittsburghPA15213 United States

The advancement of Speech Emotion Recognition (SER) is significantly dependent on the quality of emotional speech corpora used for model training. Researchers in the field of SER have developed various corpora by adjusting design parameters to enhance the reliability of the training source. For this study, we focus on exploring communication modes of collection, specifically analyzing spontaneous emotional speech patterns gathered during conversation or monologue. While conversations are acknowledged as effective for eliciting authentic emotional expressions, systematic analyses are necessary to confirm their reliability as a better source of emotional speech data. We investigate this research question from perceptual differences and acoustic variability present in both emotional speeches. Our analyses on multi-lingual corpora show that, first, raters exhibit higher consistency for conversation recordings when evaluating categorical emotions, and second, perceptions and acoustic patterns observed in conversational samples align more closely with expected trends discussed in relevant emotion literature. We further examine the impact of these differences on SER modeling, which shows that we can train a more robust and stable SER model by using conversation data. This work provides comprehensive evidence suggesting that conversation may offer a better source compared to monologue for developing an SER model. © 2010-2012 IEEE.

关键词： Speech analysis

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Efficient Collaborative Rule Caching Through Pairing of P4 Switches in SDNs

Efficient Collaborative Rule Caching Through Pairing of P4 S...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Saberi, Mohammad Dolati, Mahdi Movaghar, Ali Dargahi, Tooska Khonsari, Ahmad Sharif University of Technology Department of Computer Engineering Tehran Iran Manchester Metropolitan University Manchester United Kingdom University of Tehran Department of Electrical and Computer Engineering Tehran Iran Institute for Research in Fundamental Sciences School of Computer Science Tehran Iran

ISBN: (纸本)9798350351255

Software-defined networks (SDNs) provide customizable traffic control by storing numerous rules in on-chip memories with minimal access latency. However, the current on-chip memory capacity falls short of meeting the growing demands of SDN control applications. While rule eviction and aggregation strategies address this challenge at the switch level, programmable data planes enable a more flexible approach through cooperative rule caching. However, current solutions rely on computationally intensive off-the-shelf solvers to perform rule placement across the network. In this paper, we present an efficient solution for the cooperative rule caching problem. We first present the design of a resource-efficient switch capable of caching rules for its neighbors alongside a lightweight protocol for retrieving cached rules. Then, we introduce RaSe, an approximation algorithm for minimizing rule lookup latency across the network through optimized cooperation-aware rule placement. We conduct a theoretical analysis of RaSe, followed by a P4-based proof-of-concept assessment in Mininet and a large-scale numerical evaluation using real-world network topology. In comparison with existing solver-based solutions, the proposed method obtains the solution 160 times faster and improves the average rule lookup latency by about 21% compared to several algorithmic baselines. © 2024 IEEE.

关键词： Approximation algorithms

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Multiband strain balanced superlattice material system for third generation infrared detectors

Multiband strain balanced superlattice material system for t...

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2024 IEEE Research and Applications of Photonics in Defense Conference, RAPID 2024

作者： Dehzangi, Arash Robert R. McCormick School of Engineering and Applied Science Northwestern University Department of Electrical and Computer Engineering EvanstonIL United States

ISBN: (纸本)9798350373097

Recent increasing interest in strain balanced Type-II superlattices material causing close attention from industry. Tremendous investment was drawn toward establishing strain balanced superlattice (SLS) as new alternative for infrared photodetectors across the broad range of infrared spectrum. In recent years, SLS material system has shown capability in particular specifications to compete with mature and standard mercury cadmium telluride for mid-wavelength and long-wavelength infrared detection. It has been great interest in SLS material system for applications aligned with the standard of third generation of infrared detectors. In this presentation, some recent progress in three color infrared photodetectors based on SLS material system will be presented. © 2024 IEEE.

关键词： Infrared detectors

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Dynamical Selective Image Encryption Using Chaos 9

Dynamical Selective Image Encryption Using Chaos

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9th International Conference on Integrated Circuits, Design, and Verification, ICDV 2024

作者： Hoang, Thang Manh Hoang, Manh-Hai Pham, Quang-Anh Hanoi University of Science and Technology School of Electrical and Electronic Engineering Hanoi Viet Nam University of Alberta Department of Computer Science Edmonton Canada

ISBN: (纸本)9798350371864

Image data has been increasingly generated by cameras as well as acquisition modalities. Image data is diverse and has different sensitive levels. Encryption algorithms for massive image data are required not only high confidential but also high speed. Sometimes, the trade-off between the speed and confidentiality of an encryption occurs for image data, and it can be obtained with selective image encryption. However, most of existing selective image encryption algorithms are with fixed values of parameters, as a consequence, the confidentiality is threatened from cryptanalysis methods. In this paper, the scheme of selective image encryption using chaos is proposed, in which its parameters are changed dynamically. Specifically, the diffusion is carried out with dynamically selected pixels, and on its varying number of significant bits. The permutation performs on blocks of selected pixels with varying size. Intuitively, the security of the proposed scheme is improved by dynamical selective of data for the encryption. The exemplar simulation shows the effectiveness of the proposed scheme with security analysis by means of testing entropy, and correlation between neighbor pixels. The amount of data to be encrypted is also measured in compared with existing selective image encryption. © 2024 IEEE.

关键词： Pixels

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Identification and ranking biomaterials for bone scaffolds using machine learning and PROMETHEE

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Research on Biomedical engineering 2023年第1期39卷 129-138页

作者： Javaid, Sabah Gorji, Hamed Taheri Soulami, Khaoula Belhaj Kaabouch, Naima Department of Biomedical Engineering University of North Dakota Grand ForksND United States School of Electrical Engineering and Computer Science Grand ForksND United States Rabat Morocco

Purpose: Bones have a complex hierarchical structure that supports their diverse chemical, biological, and mechanical functions. High rates of bone susceptibility to fractures and injury have attracted extensive research interest to find alternate biomaterials for bone scaffolds. Natural bone healing is only successful if the defect is very small and when a defect exceeds 1 cm3 then bone grafting is required. Large bone defects or injuries are very serious problems in orthopedics as they bring great harm to health and normal function of daily life routine. A scaffold should have good strength to maintain its own structure after implantation in a load bearing environment and without being stiff that shields surrounding bone from the load. Therefore, mechanical properties of bone scaffolds should match those of the host tissue and should be part of the natural environment of the body without any harm or further damage. Methods: In this paper, we present two main contributions. First, we investigate the use of machine learning models in identifying biomaterials that are suitable for bone scaffolds. Second, we rank the best materials for biomedical scaffold applications using the multi-criteria decision analysis methods, the Preference Ranking Organization METhod for the Enrichment of Evaluations (PROMETHEE). Machine learning models investigated are AdaBoost, artificial neural network (ANN), Naïve Bayes (NB), Decision tree (DT), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN). Mechanical properties such as comprehensive strength, tensile strength, and Young’s modulus with the cortical bone are used as the standard reference for classification. Results: The results show that the ANN outperforms the other machine learning models in identifying the biomaterials suitable for bone tissue engineering, while the ranking results using PROMETHEE show that Brushite and Titanium alloy are the best appropriate biomaterials for the cancellous and cortical bones, respectiv

关键词： Decision trees

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Bubble-Wave-Mitigation Algorithm and Transformer-Based Neural Network Demodulator for Water-air Optical Camera Communications

IEEE Photonics Journal

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IEEE Photonics Journal 2023年 1-10页

作者： Li, Maolin Ling, Peng Wen, Shangsheng Chen, Xiandong Wen, Fei School of Automation Science and Engineering South China University of Technology Guangzhou Guangdong China Department of Electrical and Computer Engineering Texas A&M University College Station TX USA

Optical camera communication (OCC) has been widely employed in various applications as a flexible and cost-effective means of communication both on land and underwater. However, the performance of the OCC system through the water-air interface has not been thoroughly investigated. In this paper, we explore the performance of the OCC system in a water-air environment and propose a bubble-wave-mitigation algorithm to pre-process the captured frames of received video. Moreover, we propose a transformer-based neural network to demodulate the transmitted signal, mitigating the deterioration in transmission performance caused by inter-symbol interference (ISI). The experimental results demonstrate that a robust transmission can be achieved in the water-air environment by applying our proposed algorithms and neural network demodulator. Author

关键词： Cost effectiveness

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Time-Invariant Beampattern Design in Frequency Diverse Array Radar: Some New Results 4

Time-Invariant Beampattern Design in Frequency Diverse Array...

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4th International Conference on Digital Futures and Transformative Technologies, ICoDT2 2024

作者： Shaiza Ahmed, Obaidullah Ali, Hussain Zaib, Alam Ahmed, Sajid National University of Sciences and Technology School of Electrical Engineering and Computer Science Islamabad Pakistan National University of Sciences and Technology Department of Electrical Engineering Military College of Signals Islamabad Pakistan COMSATS University Islamabad Department of Electrical and Computer Engineering Islamabad Abbottabad22060 Pakistan King Abdullah University of Science and Technology Computer Electrical and Mathematical Sciences and Engineering Division Thuwal23955-6900 Saudi Arabia

ISBN: (纸本)9798350391862

A new frequency diverse array (FDA) radar system is proposed for range estimation of a target using time-invariant beampattern. To illuminate a desired range, the transmit beampattern is optimized using the inverse fast Fourier transform (IFFT) technique. This allows for a longer dwell period, which improves the accuracy of weak target identification. To lessen noise effects in range estimation, the minimum power distortionless response (MPDR) beamformer is employed. The precision of range estimation is derived using the Cramér-Rao lower bound (CRLB). Based on simulation data, the FDA design that has been proposed performs better than current approaches as measured by the root-mean-squared error (RMSE). The proposed FDA radar shows superior target localization performance compared to existing techniques, achieving the CRLB at a signal-to-noise (SNR) value of -5 dB. © 2024 IEEE.

关键词： Mean square error

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