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14th International Conference on computer and Knowledge engineering, ICCKE 2024

作者： Habibi, Afsaneh Taghiyareh, Fattaneh Department of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9798331511272

What makes a good conversation? The answer is complex and multifaceted. We propose a tool that automatically detects good conversations based on the Cooperative Principle criteria. While previous research has mainly focused on how social media affordances impact conversation quality, we focus on the user's role. We aim to understand how user adherence to these quality measures influences the responses they receive. Our data from Reddit indicates a weak to moderate correlation between a user's adherence to conversation quality measures (notably politeness and justification) and the quality of responses they receive. Underscoring an individual user's significant influence on the overall quality of social media interactions and highlighting the potential for users to positively change the course of conversations. ©2024 IEEE.

关键词： component computer-mediated communication conversation cooperative principle social media

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DNN Hardware Accelerator Selection for Feasible Deployment of MARL-Based MAC Protocols in Industrial IoT Networks 8

DNN Hardware Accelerator Selection for Feasible Deployment o...

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8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024

作者： Russo, Enrico Vinciguerra, Elio Ascia, Giuseppe Panno, Daniela University of Catania Department of Electrical Electronics and Computer Engineering Italy

ISBN: (纸本)9798350362138

The future wireless industrial Internet of Things (IIoT) networks are characterized by very stringent quality of service (QoS) requirements, which impose innovative solutions for the medium access control (MAC) communication protocols. For this reason, the research topic of automatically learning a MAC protocol via the multi-agent reinforcement learning (MARL) paradigm has been receiving much attention. Although proposals available in the literature demonstrate promising performance in simulation results, these solutions may not be easily implementable in real-world scenarios due to the stringent limitations of IoT devices (IoTD) in making deep neural network (DNN) inferences timely and energy-efficient. In this paper, we focus on this feasibility problem. Instead of relying on energy-inefficient CPUs or GPUs for inference, we adopt DNN hardware accelerators embedded into energy-constrained IoTDs to execute DNN computations. However, this solution is not straightforward since a DNN accelerator exposes many configurable hardware settings that the designer has to properly set. To address this problem, we present a novel criterion for selecting the optimal accelerator instance, foreseeing exploration of the design space of configurable DNN accelerators while considering deployment key performance indicators (KPIs) such as inference latency and energy consumption, and chip area. Then, among the accelerator instances that fulfill the deployment KPIs, our criterion enables the selection of the optimal accelerator taking also into account the communication KPIs of the MAC protocol. © 2024 IEEE.

关键词： Quality of service

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EV Battery Modeling and Optimisation for Different Drive Cycles Using MATLAB

EV Battery Modeling and Optimisation for Different Drive Cyc...

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2024 International Conference on electrical and computer engineering Researches, ICECER 2024

作者： Mangara, Bernard Tonderayi Department of Electrical Electronic and Computer Engineering Bloemfontein South Africa

ISBN: (纸本)9798331539733

Optimizing the performance of electric vehicle (EV) batteries is essential to improve efficiency and prolong the lifespan of EVs. This research introduces a simulation model based on MATLAB to analyze and enhance lithium-ion battery performance under different driving conditions inclusive of urban, highway and mixed scenarios. The model takes into consideration battery metrics like capacity, energy density, power density and cycle life. By assessing how different driving patterns impact battery performance, energy consumption, and thermal regulation the study aims to pinpoint the driving cycle that minimizes energy consumption while maximizing battery longevity. The methodology involves using a gradient descent optimization method to determine the optimal driving cycle. The findings illustrate energy consumption levels and projected battery lifespan for each driving cycle offering insights for refining strategies related to managing EV batteries. © 2024 IEEE.

关键词： MATLAB

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Image Compression via Alternating Least Squares

Image Compression via Alternating Least Squares

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2024 International Conference on IT and Industrial Technologies, ICIT 2024

作者： Zeeshan, Muhammad Department of Electrical and Computer Engineering Air University Islamabad Pakistan

ISBN: (纸本)9798331504465

In numerous application areas such as medical imaging and remote sensing, image compression methods play an important role in managing data storage and transmission costs. In this paper, we present an empirical study on a low-rank approximation using the alternating least squares (ALS) method for image compression. For high-dimensional data, we demonstrate the advantage of a matrix decomposition-based implementation that avoids explicit matrix inversion applied in the direct implementation in terms of computational efficiency. The performance of the ALS method is compared with the singular value decomposition in terms of information loss, and compression ratio. © 2024 IEEE.

关键词： Singular value decomposition

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Towards Robust Multi-Camera Object Tracking: A Framework for Global Coordination and ID Consistency 29

Towards Robust Multi-Camera Object Tracking: A Framework for...

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29th International Conference on Information Technology, IT 2025

作者： Kim, Eun Ho Choi, Yeong Gwang Suh, Young Hoon Jeon, Jae Wook Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798331517649

This study presents a structured framework for a scalable multi-camera tracking system based on ROS2, focusing on architectural design rather than experimental validation. The proposed system is designed to easily integrate different cameras and objects by utilizing the modular structure of ROS2 and can maintain reliable tracking performance even in complex environments. In particular, it adopts a global coordinate system transformation and an identity matching method based on the Hungarian algorithm to effectively maintain the consistency of identities between objects even in the presence of overlapping fields of view (FoV) and an increasing number of objects. This approach is shown to be an efficient and scalable solution for various multi-camera-based applications such as traffic monitoring, and autonomous driving. © 2025 IEEE.

关键词： Object detection

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Boosting Indoor Localization and Identification Speed Using Reflection Map Construction 100

Boosting Indoor Localization and Identification Speed Using ...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Johnny, Milad Valaee, Shahrokh University of Toronto Electrical and Computer Engineering Department Toronto Canada

ISBN: (纸本)9798331517786

This paper proposes an indoor localization strategy that utilizes fixed reflector points. The strategy assumes the presence of a base station (BS) with a known location, equipped with Angle of Arrival (AoA) and Time of Arrival (ToA) measurement capabilities. The localization process comprises two stages. In the initial stage, a systematic environmental scan identifies reflector points, facilitating the creation of a detailed map of their locations. Next, to achieve precise localization, a maximization problem is formulated. For each candidate location, the method assesses the likelihood of a set of measurements to the reflectors map. This approach accelerates user localization compared to fingerprint search algorithms. Simulation results provide compelling evidence for the effectiveness of this strategy in speeding up data gathering in the localization procedure. © 2024 IEEE.

关键词： Indoor positioning systems

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Exploring Noise- Resilient Spiking Neural Encoding using ∑†∑ Neurons 67

Exploring Noise- Resilient Spiking Neural Encoding using ∑...

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67th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2024

作者： Sreekumar, R. Mullick, Faiyaz E. Morshed, Md Golam Ghosh, Avik W. Stan, Mircea R. University of Virginia Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798350387179

Researchers are increasingly focusing on spiking neurons to enhance the energy efficiency of edge machine learning (ML) models. Spiking neural encoding has evolved from traditional methods like Integrate and Fire and Time to First Spike to techniques such as Delta and Sigma-delta modulation (SD), enabling sparser and energy-efficient feature representation. In this work, we introduce the Sigma-Delta-Sigma (∑†∑/SDS) neuron, a noise-invariant spiking neural encoding technique. Our aim with this neural encoding is to emulate the robustness of a specific class of biological neurons to input noise by effectively filtering out noise-like features from the input stimuli. While noise injection in training prevents overfitting, improper noise profiles can be detrimental to the inference accuracy of a model. Our objective with the SDS encoding is to develop noise-resilient spiking neural network models capable of being trained with ideal features, while still being able to extract features from low-quality data during the inference phase. To assess the robustness of our technique, we implement an information encoding ensemble model that demonstrates a 6.2x improvement in robustness when the Signal-to-Noise Ratio (SNR) of the incoming signal is 1 dB. Furthermore, we evaluate the performance of the SDS neurons in more complex models such as a Liquid State Machine (LSM), where the model exhibits a 3.87% improvement in the predictive accuracy against the baseline model when tested against input features with SNR degradation from 55 to 1 dB. © 2024 IEEE.

关键词： Energy efficiency

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Plasmonic Au Decorated CdS Nanowire Arrays for Enhanced Photoelectrochemical Hydrogen Evolution

Plasmonic Au Decorated CdS Nanowire Arrays for Enhanced Phot...

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2024 Photonics North, PN 2024

作者： Alam, Kazi M. Chaulagain, Narendra Manuel, Ajay P. Shankar, Karthik Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

ISBN: (纸本)9798350366365

In this work, an exciton-plasmon coupled system comprising hexagonal CdS nanowire and Au nanoparticle has been synthesized, characterized and tested in photoelectrochemical (PEC) water-splitting experiment. The significantly improved device performance of the Au@CdS hybrid in comparison to that of bare CdS nanowires has been primarily attributed to plasmon-induced hot electron injection from Au nanoparticles into adjacent CdS nanowires. © 2024 IEEE.

关键词： Nanowires

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Inverse Reticle Optimization with Quantum Annealing and Hybrid Solvers

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IEEE Access 2024年 12卷 33069-33078页

作者： Fang, Po-Hsun Chen, Yan-Syun Wu, Jhih-Sheng Yu, Peichen National Yang Ming Chiao Tung University College of Electrical and Computer Engineering Department of Photonics Hsinchu30010 Taiwan

Reticle optimization is a computationally demanding task in optical microlithography for advanced semiconductor fabrication. In this study, we explore the effectiveness of D-Wave's quantum annealing (QA) and hybrid steepest descent (SD) solvers in solving pixelated binary reticle optimization problems. We show that the energy derived from the objective function depends on annealing time and inter-sample correlation. Specifically, longer annealing times and reduced inter-sample correlations result in lower energy. Moreover, introducing efficient pausing strategies in forward annealing could reduce the QA runtime by approximately 100-fold while achieving similar results to long annealing times. Finally, reticles with increased variables lead to widespread irregular values in default sorted QA energies due to quantum chain breakages, which could potentially limit the probability of attaining the optimal solution. A hybrid approach that applies the classical SD algorithm to the QA results increases the probability of locating the global minimum solution and reduces runtime to about one-third compared to the classical SD solver. These findings facilitate our comprehension of quantum computing for accelerating computational lithography in semiconductor manufacturing. © 2013 IEEE.

关键词： Linear programming

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Overall Performance Improvement of Radiation-Hardened SRAM Cells through Assist Techniques 12

Overall Performance Improvement of Radiation-Hardened SRAM C...

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12th International Conference on Internet of Everything, Microwave, Embedded, Communication and Networks, IEMECON 2024

作者： Patil, Akshat Raj Vattoly, Abin Rathore, Nitesh Kumar Singh, Pooran Department of Electrical and Computer Engineering Mahindra University Hyderabad India

ISBN: (纸本)9798350387315

The harsh environment in space is characterized by high-energy particles and extreme temperature swings, which can cause single event upsets (SEUs) in conventional 6T SRAM cells. These cells are not resistant to SEUs and have a low critical charge (Qc), making them unsuitable for use in space applications. Radiation-hardened SRAM (RHSRAM) cells are an alternative to conventional SRAM cells, as they are resistant to SEUs and can recover from soft errors on their own. Researchers have proposed many different RHSRAM cells over the years, including the RHBD 10T, RHMD 10T, SRRD 12T, and RHPD 12T cells. This paper presents a simulation and estimation of the design metrics of these four RHSRAM cells. The results show that the SRRD 12T cell has the best overall performance, with the highest EQM (error-free memory) value. Finally, the paper proposes read/write assist techniques to improve the read/write design metrics of the RHSRAM cells. These techniques are shown to further improve the overall EQM value of the SRRD 12T cell. © 2024 IEEE.

关键词： Radiation hardening

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