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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Patel, Parth Hasan, Syed Rafay Rahman, Mohammad Ashiqur Homsi, Soamar Tennessee Tech University Department of Electrical and Computer Engineering United States Florida International University Department of Computer Science United States AirForce Research Laboratory Information Warfare Division United States

ISBN: (纸本)9798331517786

Although Collaborative Deep Neural Network (CDNN) promises to be an alternative mechanism to mitigate the effects of the untrusted cloud, this approach is susceptible to other kinds of adversarial attacks, which arise from one or more untrusted devices in CDNN acting maliciously. However, since each untrusted node in the CDNN contains only partial information of the complete DNN model, it is worth investigating whether the attacker can still muster a viable threat to CDNN or not. This led to the investigation of attack scenarios and their effects on convolutional neural networks (CNN) used for image classification in the CDNN environment. In this research, we are investigating the shortcomings of existing attacks on CDNN, that lead to non-subtle attack to the defender who is on look out against such attacks. Our research showed that sparse nature of feature maps (FMs) due to the ReLU function lead to many existing attacks more obvious to the attacker. Next, we investigated how one can detect the existing attacks if the defender has some previous knowledge of the complete CNN's FMs. Our results show minimal detection overhead of about 2%, with an accuracy of 95% and F1 score of above 0.97. © 2024 IEEE.

关键词： Convolutional neural networks

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Fixed-time-synchronized control: a system-dimension-categorized approach

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Science China(Information Sciences) 2023年第7期66卷 177-194页

作者： Wanyue JIANG Shuzhi Sam GE Dongyu LI Institute for Future & Shandong Key Laboratory of Industrial Control Technology School of Automation Qingdao University Department of Electrical and Computer Engineering National University of Singapore School of Cyber Science and Technology Beihang University Shanghai Institute of Satellite Engineering

This study addresses the fixed-time-synchronized control problem of perturbed multi-input multioutput(MIMO) systems. In the task of fixed-time-synchronized control, different dimensions of the output signal in MIMO systems are required to reach the desired value simultaneously within a fixed time *** MIMO system is categorized into two cases: the input-dimension-dominant and the state-dimensiondominant cases. The classification is defined according to the dimension of system signals and, more importantly, the capability of converging at the same time. For each kind of MIMO system, sufficient Lyapunov conditions for fixed-time-synchronized convergence are explored, and the corresponding robust sliding mode controllers are designed. Moreover, perturbations are compensated using the super-twisting technique. The brake control of the vertical takeoff and landing aircraft is considered to verify the proposed method for the input-dimension-dominant case, which shows the essential advantages of decreasing the energy consumption and the output trajectory length. Furthermore, comparative numerical simulations are performed to show the semi-time-synchronized property for the state-dimension-dominant case.

关键词： fixed-time-synchronized convergence sliding mode control perturbed MIMO systems

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LibMTL: A Python Library for Deep Multi-Task Learning

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Journal of Machine Learning Research 2023年第1期24卷 1-7页

作者： Lin, Baijiong Zhang, Yu The Hong Kong University of Science and Technology Guangzhou China Department of Computer Science and Engineering Southern University of Science and Technology Peng Cheng Laboratory China

This paper presents LibMTL, an open-source Python library built on PyTorch, which provides a unified, comprehensive, reproducible, and extensible implementation framework for Multi-Task Learning (MTL). LibMTL considers different settings and approaches in MTL, and it supports a large number of state-of-the-art MTL methods, including 13 optimization strategies and 8 architectures. Moreover, the modular design in LibMTL makes it easy to use and well extensible, thus users can easily and fast develop new MTL methods, compare with existing MTL methods fairly, or apply MTL algorithms to real-world applications with the support of LibMTL. The source code and detailed documentations of LibMTL are available at https://***/median-research-group/LibMTL and https://***, respectively. ©2023 Baijiong Lin and Yu Zhang.

关键词： Python

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Crosstalk Impact on CMOS Low Noise Amplifiers from RF to millimeter Wave

Crosstalk Impact on CMOS Low Noise Amplifiers from RF to mil...

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2024 Panhellenic Conference on Electronics and Telecommunications, PACET 2024

作者： Themeli, R. Zachos, N. Noulis, T. Pavlidis, V.F. Hatzopoulos, A. Aristotle University of Thessaloniki Electronics Laboratory Department of Physics 54124 Greece Aristotle University of Thessaloniki Electronics Laboratory Department of Electrical and Computer Engineering 54124 Greece

ISBN: (纸本)9798350318845

This work addresses crosstalk effects on three low noise amplifiers (LNAs) operating at different frequency bands, the S-band (2.4 GHz), the Ka-band (28 GHz), and the V-band (56 GHz). The LNAs were implemented using a 22nm FDSOI process and were extracted both as stand-alone circuits and considering operation onto the same die. The passive components were extracted using Ansys RaptorX. As to address the consequences of crosstalk on the LNA performance specific performance metrics, such as gain (S21), input matching (S11), noise figure (NF), linearity (1 dB Compression Point and Third Point Intercept) and power dissipation (Pdc), were studied for each frequency band LNA and compared with their performance when they were operating onto the same die. © 2024 IEEE.

关键词： Crosstalk

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A Simple but Effective Approach for Unsupervised Few-Shot Graph Classification 24

A Simple but Effective Approach for Unsupervised Few-Shot Gr...

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33rd ACM Web Conference, WWW 2024

作者： Liu, Yonghao Huang, Lan Cao, Bowen Li, Ximing Giunchiglia, Fausto Feng, Xiaoyue Guan, Renchu College of Computer Science and Technology Jilin University Changchun China Department of Information Engineering and Computer Science University of Trento Trento Italy Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education China

ISBN: (纸本)9798400701719

Graphs, as a fundamental data structure, have proven efficacy in modeling complex relationships between objects and are therefore found in wide web applications. Graph classification is an essential task in graph data analysis, which can effectively assist in extracting information and mining content from the web. Recently, few-shot graph classification, a more realistic and challenging task, has garnered great research interest. Existing few-shot graph classification models are all supervised, assuming abundant labeled data in base classes for meta-training. However, sufficient annotation is often challenging to obtain in practice due to high costs or demand for expertise. Moreover, they commonly adopt complicated meta-learning algorithms via episodic training to transfer prior knowledge from base classes. To break free from these constraints, in this paper, we propose a simple yet effective approach named SMART for unsupervised few-shot graph classification without using any labeled data. SMART employs transfer learning philosophy instead of the previously prevailing meta-learning paradigm, avoiding the need for sophisticated meta-learning algorithms. Additionally, we adopt a novel mixup strategy to augment the original graph data and leverage unsupervised pretraining on these data to obtain the expressive graph encoder. We also utilize the prompt tuning technique to alleviate the overfitting and low fine-tuning efficiency caused by the limited support samples of novel classes. Extensive experimental results demonstrate the superiority of our proposed approach, significantly surpassing even leading supervised few-shot graph classification models. Our code is available here. © 2024 ACM.

关键词： Graph neural networks

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PointPillars Backbone Type Selection for Fast and Accurate LiDAR Object Detection

PointPillars Backbone Type Selection for Fast and Accurate L...

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International Conference on computer vision and Graphics, ICCVG 2022

作者： Lis, Konrad Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland

ISBN: (纸本)9783031220241

3D object detection from LiDAR sensor data is an important topic in the context of autonomous cars and drones. In this paper, we present the results of experiments on the impact of backbone selection of a deep convolutional neural network on detection accuracy and computation speed. We chose the PointPillars network, which is characterised by a simple architecture, high speed, and modularity that allows for easy expansion. During the experiments, we paid particular attention to the change in detection efficiency (measured by the mAP metric) and the total number of multiply-addition operations needed to process one point cloud. We tested 10 different convolutional neural network architectures that are widely used in image-based detection problems. For a backbone like MobilenetV1, we obtained an almost 4x speedup at the cost of a 1.13% decrease in mAP. On the other hand, for CSPDarknet we got an acceleration of more than 1.5x at an increase in mAP of 0.33%. We have thus demonstrated that it is possible to significantly speed up a 3D object detector in LiDAR point clouds with a small decrease in detection efficiency. This result can be used when PointPillars or similar algorithms are implemented in embedded systems, including SoC FPGAs. The code is available at https://***/vision-agh/pointpillars-backbone. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object detection

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PHUI-GA: GPU-based efficiency evolutionary algorithm for mining high utility itemsets

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Journal of Systems engineering and Electronics 2024年第4期35卷 965-975页

作者： JIANG Haipeng WU Guoqing SUN Mengdan LI Feng SUN Yunfei FANG Wei Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence Department of Computer Science and TechnologyJiangnan UniversityWuxi 214122China China Ship Scientific Research Center Wuxi 214082China Taihu Laboratory of Deepsea Technological Science Wuxi 214082China Department of Mathematics Nanjing UniversityNanjing 210023China

Evolutionary algorithms(EAs)have been used in high utility itemset mining(HUIM)to address the problem of discover-ing high utility itemsets(HUIs)in the exponential search *** have good running and mining performance,but they still require huge computational resource and may miss many *** to the good combination of EA and graphics processing unit(GPU),we propose a parallel genetic algorithm(GA)based on the platform of GPU for mining HUIM(PHUI-GA).The evolution steps with improvements are performed in central processing unit(CPU)and the CPU intensive steps are sent to GPU to eva-luate with multi-threaded *** show that the mining performance of PHUI-GA outperforms the existing *** mining 90%HUIs,the PHUI-GA is up to 188 times better than the existing EAs and up to 36 times better than the CPU parallel approach.

关键词： high utility itemset mining(HUIM) graphics process-ing unit(GPU)parallel genetic algorithm(GA) mining perfor-mance

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Assessing the Viability of AC to DC Microgrid Conversion: A Comprehensive Analysis of Technical and Economic Factors 59

Assessing the Viability of AC to DC Microgrid Conversion: A ...

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59th International Universities Power engineering Conference, UPEC 2024

作者： Charalambous, Chrysanthos Polycarpou, Alexis Efthymiou, Venizelos Georghiou, George E. University of Cyprus Pv Technology Laboratory Department Of Electrical and Computer Engineering Cyprus Phaethon Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus Frederick University Department of Electrical Computer Engineering and Informatics Nicosia Cyprus

ISBN: (纸本)9798350379730

In the face of global warming and the acceleration of climate changes, urgent and decisive measures must be taken to mitigate these phenomena. This study addresses this urgent need by exploring the transition from traditional AC distribution systems to more efficient DC and hybrid AC/DC systems, recognizing the utmost importance of both technical developments and economic considerations. Through a thorough overview of existing literature and empirical knowledge gathered from the nanogrid of FOSS Research Centre for Sustainable Energy of University of Cyprus, this research clarifies the inherent advantages of DC and AC/DC hybrid systems. In addition, it presents a detailed case study for the comprehensive assessment of the feasibility and effectiveness of these systems. The preliminary economic analysis carried out in this study demonstrates the cost-effectiveness and performance improvements offered by hybrid AC/DC microgrids compared to conventional AC configurations. According to the findings of this work it is obvious that the ROI increases with the increase of DC loads over AC loads until the case where DC loads reach the 75% of the total load (ROI=13.9%). However, even in the case of Full DC microgrid, the ROI is higher by 1% compared to the case of Full AC microgrid thus significantly reducing the payback period. These findings not only underline the urgency of the transition to more efficient and sustainable energy distribution systems, but also provide valuable information for policymakers, industry stakeholders and researchers. By embracing these innovative technologies, a more resilient and environmentally responsive energy infrastructure can be promoted that is in line with the demands of a rapidly changing global climate. © 2024 IEEE.

关键词： Clean energy

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Parity-check and G-matrix based intelligent early stopping criterion for belief propagation decoder for polar codes

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Digital Communications and Networks 2023年第5期9卷 1148-1156页

作者： Qasim Jan Shahid Hussain Zhiwen Pan Nan Liu Zakir Ali Zechen Liu Xiaohu You National Mobile Communications Research Laboratory Southeast UniversityNanjingJiangsu210096China Purple Mountain Laboratories NanjingJiangsu211100China Department of Computer Science COMSATS University IslamabadAttock CampusAttock43600Pakistan School of Medicine Computer Science and EngineeringUniversity of GalwayH91 TK33GalwayIreland Department of Computer Sciences Bahria University Lahore Campus54600Pakistan

The error correction performance of Belief Propagation(BP)decoding for polar codes is satisfactory compared with the Successive Cancellation(SC)***,it has to complete a fixed number of iterations,which results in high computational *** necessitates an intelligent identification of successful BP decoding for early termination of the decoding process to avoid unnecessary iterations and minimize the computational complexity of BP *** paper proposes a hybrid technique that combines the“paritycheck”with the“G-matrix”to reduce the computational complexity of BP decoder for polar *** proposed hybrid technique takes advantage of the parity-check to intelligently identify the valid codeword at an early stage and terminate the BP decoding process,which minimizes the overhead of the G-matrix and reduces the computational complexity of BP *** explore a detailed mechanism incorporating the parity bits as outer code and prove that the proposed hybrid technique minimizes the computational complexity while preserving the BP error correction ***,mathematical formulation for the proposed hybrid technique that minimizes the computation cost of the G-matrix is *** performance of the proposed hybrid technique is validated by comparing it with the state-of-the-art early stopping criteria for BP *** results show that the proposed hybrid technique reduces the iterations by about 90%of BP decoding in a high Signal-to-Noise Ratio(SNR)(i.e.,3.5~4 dB),and approaches the error correction performance of G-matrix and conventional BP decoder for polar codes.

关键词： Belief propagation Early termination G-matrix Parity-check Polar codes

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A 4-bit 28-GS/s 4×Time-Interleaved Current-Steering DAC for High-Speed Interfacing

A 4-bit 28-GS/s 4×Time-Interleaved Current-Steering DAC for...

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2024 Panhellenic Conference on Electronics and Telecommunications, PACET 2024

作者： Michailidis, A. Noulis, T. Pavlidis, V.F. Hatzopoulos, A. Aristotle University of Thessaloniki Electronics Laboratory Department of Physics 54124 Greece Aristotle University of Thessaloniki Electronics Laboratory Department of Electrical and Computer Engineering 54124 Greece

ISBN: (纸本)9798350318845

In this work, a fully integrated 4-bit current-steering DAC was implemented into silicon using a 22nm SoI CMOS process node. By exploiting the time-interleaved design approach, a sampling frequency of 28-GS/s was achieved, enabling high-speed interfacing capabilities between analog and digital circuitry. The time-interleaved design approach, proposed in this work, uses an insightful current superposition technique, extending the time-interleaved factor barrier while maintaining high signal integrity and high conversion linearity, without compromising the spectral content of the output signal. For validation purposes of the proposed design approach, RLCk-aware parasitic extraction of the physical layout using Ansys RaptorX was employed and RLCk-aware simulations of the full design were performed. The performance degradation due to physical layout parasitics was compared with the schematic-view simulation scheme of the full design and it was quantified by monitoring the ENOB, SINAD and SFDR dynamic metrics of the design. © 2024 IEEE.

关键词： current superposition current-steering DAC time-interleaved transconductance amplifiers

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