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24th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2023

作者： Toka, Mesut Kaushik, Aryan Armada, Ana Garcia Shin, Wonjae Ajou University Department of Electrical and Computer Engineering Korea Republic of University of Sussex School of Engineering and Informatics Brigthon BN1 9RH United Kingdom Universidad Carlos Iii de Madrid Department of Signal Theory and Communications Leganés28911 Spain

ISBN: (纸本)9781665496261

In this paper, we analyze the outage behavior of a reconfigurable intelligent surface (RIS)-aided low earth orbit (LEO) satellite network based on orthogonal frequency division multiplexing (OFDM). In the satellite network, a RIS node with multiple reflecting elements is deployed between the satellite and ground user since there are strong blockages in the line-of-sight link. Due to the very high velocity of the LEO satellite, the satellite-RIS link suffers from a severe Doppler shift. We propose deploying the RIS node between the satellite and ground user to overcome the performance degradation caused by the Doppler shift in the satellite link. To evaluate the system performance, we obtain an approximated closed-form outage probability (OP) expression corresponding to any sub-carrier. Also, an asymptotic expression for the obtained OP is provided to present further insights. The theoretical results validated by the Monte Carlo simulations demonstrate that the effects of the Doppler shift can be significantly decreased as the number of RIS elements and sub-carrier spacing are increased. © 2023 IEEE.

关键词： Orthogonal frequency division multiplexing

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Mini-InternVL: a flexible-transfer pocket multi-modal model with 5% parameters and 90% performance

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Visual Intelligence 2024年第1期2卷 1-17页

作者： Gao, Zhangwei Chen, Zhe Cui, Erfei Ren, Yiming Wang, Weiyun Zhu, Jinguo Tian, Hao Ye, Shenglong He, Junjun Zhu, Xizhou Lu, Lewei Lu, Tong Qiao, Yu Dai, Jifeng Wang, Wenhai Shanghai AI Laboratory Shanghai 200232 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China School of Computer Science Nanjing University Nanjing 210023 China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen 518055 China School of Computer Science Fudan University Shanghai 200433 China SenseTime Research Shanghai 200233 China Department of Electronic Engineering Tsinghua University Beijing 100084 China Beijing National Research Center for Information Science and Technology Department of Automation Tsinghua University Beijing 100084 China Department of Information Engineering The Chinese University of Hong Kong 999077 Hong Kong

Multi-modal large language models (MLLMs) have demonstrated impressive performance in vision-language tasks across a wide range of domains. However, the large model scale and associated high computational cost pose significant challenges for training and deploying MLLMs on consumer-grade GPUs or edge devices, thereby hindering their widespread application. In this work, we introduce Mini-InternVL, a series of MLLMs with parameters ranging from 1 billion to 4 billion, which achieves 90% of the performance with only 5% of the parameters. This significant improvement in efficiency and effectiveness makes our models more accessible and applicable in various real-world scenarios. To further promote the adoption of our models, we are developing a unified adaptation framework for Mini-InternVL, which enables our models to transfer and outperform specialized models in downstream tasks, including autonomous driving, medical image processing, and remote sensing. We believe that our models can provide valuable insights and resources to advance the development of efficient and effective MLLMs. © The Author(s) 2024.

关键词： Knowledge distillation Lightweight multi-modal large language model Vision-language model Visual instruction tuning

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Capacity Analysis: The potential of the wireless factory of the future

Capacity Analysis: The potential of the wireless factory of ...

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Irish Signals and Systems Conference (ISSC)

作者： William O’Brien Mihai Penica Martin Hayes Eoin O’Connell Department of Electronic & Computer Engineering University Of Limerick Limerick Ireland

The introduction of new wireless technologies is one of the requirements for the digital transformation of manufacturing technology. The implementation of wireless devices, such as smart sensors and flexible programmable robots, requires an increase in the data transfer rate, the number of wireless network nodes and, as a result, an increase in the density of the wireless data transmission channels. Often, devices use different data transfer protocols and different radio frequencies simultaneously, which may, in turn, lead to both overlap and interference of *** study will be conducted within a smart manufacturing factory cell, where network throughput, latency, and RSSI will be among the data points collected. The goal is to evaluate the effects of typical production floor activities on signal strength, throughput, and latency, such as when a robot obstructs the wireless signal. The collected RSSI values will be presented on a heatmap generated in MATLAB. The data will be gathered using equipment that is both cost-effective and readily available, making it feasible for smaller operations to perform plant analysis.

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OpticalHDC: Ultra-fast Photonic Hyperdimensional Computing Accelerator 25

OpticalHDC: Ultra-fast Photonic Hyperdimensional Computing A...

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30th Asia and South Pacific Design Automation Conference, ASP-DAC 2025

作者： Liu, Jiaqi Ma, Yiwen Department of Electronic and Computer Engineering Hong Kong Univ. of Science and Tech. Hong Kong Hong Kong Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798400706356

The demand for extensive computing resources and energy to support the increasing size of machine learning models has created a disparity between AI applications and the underlying hardware, hindering the advancement of advanced general intelligence. To address this challenge, researchers have been exploring new neuromorphic computing paradigms, among which Hyperdimensional Computing (HDC) stands out for its robustness to system noise, simplicity of operations, and high parallelism. However, accelerating the time-consuming encoding and search algorithms in HDC remains a formidable *** this paper, we propose the first Photonic Hyperdimensional Computing (HDC) accelerator to overcome the challenges of high-dimensional data processing. Our accelerator incorporates multiple Microring-based homogeneous configurable dot product cores that can be dynamically reconfigured to either the encoding stage or the classification stage. We introduce a one-to-many broadcast-based photonic computing core that leverages the wavelength-division multiplexing (WDM) and free spectral range (FSR) properties to parallel computation. Additionally, we propose a signed number operation algorithm to support the signed dot product with base hypervectors in the encoding stage. We also conduct a thorough analysis of the impact of different dimensions and encoding bit-width to ensure the reliability and robustness of our accelerator. Our experimental results demonstrate a significant speedup of up to 47.87x and 177.37x compared to state-of-the-art ASIC chips and GPUs respectively, highlighting the effectiveness of our proposed approach. © 2025 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Wavelength division multiplexing

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An Empirical Examination of the Factors of Big Data Analytics Implementation in Supply Chain Management and Logistics 10

An Empirical Examination of the Factors of Big Data Analytic...

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10th IEEE Uttar Pradesh Section International Conference on Electrical, electronics and computer engineering, UPCON 2023

作者： Ravindar, K. Syed, Mohammad Haider Sampath, Bharath Rajalakshmi, B. Reddy, V Venkat Dutt, Amit School of Sciences Sr University Telangana Warangal India Saudi Electronic University Department of Computer Science Saudi Arabia University Karnataka Bangalore India New Horizon College of Engineering Department of Computer Science Bangalore India Institute of Aeronautical Engineering Dundigal Hyderabad India Lovely Professional University Phagwara India

ISBN: (纸本)9798350382471

Numerous companies have effectively exploited Big Data Analytics (BDA) potential to enhance their effectiveness in the Big Data period. Given that big data application in logistics and supply chain management (SCM) is nevertheless in its early stages, assessments of BDA could differ from various viewpoints, producing certain difficulties in comprehending the significance and potential of big data. Based on past research on BDA and SCM, this work examines the factors that influence organizations' willingness to implement BDA in their everyday activities. This research divides potential elements into 4 groups: technical, firm, ecological, and supply chain issues. A framework consisting of direct factors like technical, firm, and mediators was presented based on the technology diffusion hypothesis. The experimental findings demonstrated that anticipated advantages and high-level management assistance might have a considerable impact on intended adoption. Furthermore, ecological variables like competitive adoption, administration legislation, and supply chain connection can greatly alter the direct connections between influencing causes and intended adoption. © 2023 IEEE.

关键词： Big data analytics Logistics Operational efficiency Supply chain management

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Enhanced Detection of Illegally Parked Vehicles Using YOLO and Good Feature to Track Methods

Enhanced Detection of Illegally Parked Vehicles Using YOLO a...

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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Fauzan Maftuh Alwafi Boby Mugi Pratama Phuong Thi Le Bima Prihasto Jia-Ching Wang Department of Informatics Institut Teknologi Kalimantan Indonesia Department of Computer Science and Information Engineering Fu Jen Catholic University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan

ISBN: (数字)9798350367331

ISBN: (纸本)9798350367348

The study addresses illegal parking, a problem that disrupts traffic and poses safety risks under Indonesia’s legal system. It proposes using the YOLO technique for detection and Optical Flow for vehicle speed assessment to identify illegally parked vehicles. The objective is to improve detection precision and efficiency in areas prone to illegal parking by leveraging deep learning, particularly Convolutional Neural Networks (CNN). The study highlights the potential of noninvasive computer vision technology to enhance public awareness and law adherence. The findings aim to support the development of a monitoring system to help law enforcement in managing illegal parking in public spaces.

关键词： YOLO Tracking Law enforcement Optical variables measurement Time measurement Safety Object recognition Convolutional neural networks Optical flow Monitoring

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Hybrid Chaotic Salp Swarm with Crossover Algorithm for Underground Wireless Sensor Networks

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computers, Materials & Continua 2022年第8期72卷 2963-2980页

作者： Mariem Ayedi Walaa H.ElAshmawi Esraa Eldesouky First Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia MEDIATRON Lab. SUP’COMCarthage UniversityTunis2083Tunisia Department of Computer Science Faculty of Computers and InformaticsSuez Canal UniversityIsmailia41522Egypt Faculty of Computer Science Misr International UniversityCairoEgypt

Resource management in Underground Wireless Sensor Networks(UWSNs)is one of the pillars to extend the network *** intriguing design goal for such networks is to achieve balanced energy and spectral resource *** paper focuses on optimizing the resource efficiency in UWSNs where underground relay nodes amplify and forward sensed data,received from the buried source nodes through a lossy soil medium,to the aboveground base station.A new algorithm called the Hybrid Chaotic Salp Swarm and Crossover(HCSSC)algorithm is proposed to obtain the optimal source and relay transmission powers to maximize the network resource *** proposed algorithm improves the standard Salp Swarm Algorithm(SSA)by considering a chaotic map to initialize the population along with performing the crossover technique in the position updates of *** experimental results,the HCSSC algorithm proves its outstanding superiority to the standard SSA for resource efficiency ***,the network’s lifetime is ***,the proposed algorithm achieves an improvement performance of 23.6%and 20.4%for the resource efficiency and average remaining relay battery per transmission,***,simulation results demonstrate that the HCSSC algorithm proves its efficacy in the case of both equal and different node battery capacities.

关键词： Underground wireless sensor networks resource efficiency chaotic theory crossover algorithm salp swarm algorithm

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BIST Design and Implementation for a Fixed-Point Arithmetic MAC Unit within a Systolic Array

BIST Design and Implementation for a Fixed-Point Arithmetic ...

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International Electrical engineering Congress (iEECON)

作者： Ian Grout Department of Electronic and Computer Engineering University of Limerick Limerick Ireland

In embedded systems involving hardware accelerators to support embedded machine learning (ML) applications, both sequential and parallel operations are used to ensure the system can perform its required operations in the required time. For ML applications involving trained ML model inference, parallel (concurrent) hardware structures can be utilized to perform parallel multiplications usually involving matrix multiplication operations in hardware rather than software. In this paper, fault simulation, embedded instrument test access and built-in self-test (BIST) are considered in relation to the multiply-accumulate (MAC) unit that would be found within a systolic array. A fault simulation was performed on the pre-synthesis MAC unit Verilog HDL design module and used to develop a BIST unit accessible via an IEEE Std 1687 network. The design was prototyped using a Xilinx Artix-7 field programmable gate array (FPGA).

关键词： Embedded systems Instruments Built-in self-test IEEE Standards Systolic arrays Circuit faults Hardware design languages

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Data Imputation Under Similarity Rule Constraints Using Fuzzy Multi-Objective Programming

Data Imputation Under Similarity Rule Constraints Using Fuzz...

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International Conference on Computational Science and Computational Intelligence (CSCI)

作者： Mohammadreza Safi Saeed Mozaffari Majid Ahmadi Shahpour Alirezaee Department of Electronic and Computer Engineering The University of Windsor Windsor Canada

ISBN: (数字)9798350361513

ISBN: (纸本)9798350372304

Missing or incomplete data poses a significant challenge during data collection for forecasting, estimation, and decision-making purposes. Given the profound impact of data quality on the performance of machine learning algorithms, data imputation plays a crucial role in many applications. Considering potential dependencies between data attributes enhances the reliability of the imputation process. In this paper, we address this by incorporating fuzzy relaxation in the differential dependencies (DDs) among attributes and propose a novel fuzzy multi-objective linear (FMOL) model to achieve optimal imputation performance. The proposed model aims to maximize the imputation rate while minimizing violations of crisp DDs. We employ the Improved Zimmermann Method to solve the FMOL model effectively. Experimental results on the Kaggle dataset demonstrate that our proposed approach outperforms existing methods in terms of imputed fields and imputation accuracy.

关键词： Machine learning algorithms Scientific computing Computational modeling Decision making Estimation Pareto optimization Imputation

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A Q- Learning and Fuzzy Logic Based Routing Protocol for UAV Networks

A Q- Learning and Fuzzy Logic Based Routing Protocol for UAV...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Sijin Huang Jie Tang Zihao Zhou Guangguang Yang Maksim V. Davydov Kai Kit Wong School of Electronic and Information Engineering South China University of Technology Guangzhou China School of electronic information engineering Foshan University Foshan China Department of Theory of Electrical Engineering Belarusian State University of Informatics and Radioelectronics Minsk Belarus Department of Electronic and Electrical Engineering University College London London UK

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

With the development of ad hoc network technol-ogy, unmanned aerial vehicle (UAV) swarm has demonstrated significant promise across civil and military domains. However, owing to unique attributions, such as high dynamic topology, 3-D mobility and low density, it's extremely challenging to establish a reliable and robust communication between flying nodes. In this paper, we proposed a Q-Learning and Fuzzy Logic based Routing Protocol (QFRP) for UAV networks, which adopted an efficient Q-value update mechanism based on HELLO and ACK. In this mechanism, we take neighbor set coherence and link lifetime into account. Since routing exploration has an important impact on routing performance, we proposed a fuzzy logic based mechanism for exploration and exploitation that considers Q-value, link quality and access delay to mitigate the blindness of random exploration. Simulation results demonstrate that QFRP can make efficient routing decisions within dynamic multi-hop UAV networks, and outperforms existing protocols regarding packet delivery ratio (PDR), end-to-end (E2E) delay, and routing overhead.

关键词： Fuzzy logic Q-learning Network topology Simulation Coherence Autonomous aerial vehicles Routing Routing protocols Delays Vehicle dynamics

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