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Combined Effect of Concept Drift and Class Imbalance on Model performance During Stream Classification

computers, Materials & Continua 2023年第4期75卷 1827-1845页

作者： Abdul Sattar Palli Jafreezal Jaafar Manzoor Ahmed Hashmani Heitor Murilo Gomes Aeshah Alsughayyir Abdul Rehman Gilal Department of Computer and Information Sciences Universiti Teknologi PETRONAS(UTP)Seri Iskandar32610Malaysia Centre for Research in Data Science UTPPerak32610Malaysia High Performance Cloud Computing Centre(HPC3) UTPPerak32610Malaysia School of Engineering and Computer Science Victoria University of WellingtonWellington6012New Zealand AI Institute University of Waikato WellingtonHamilton3240New Zealand Anti-Narcotics Force Ministry of Narcotics ControlIslamabad46000Pakistan College of Computer Science and Engineering Taibah UniversityMadinah42353Saudi Arabia

Every application in a smart city environment like the smart grid,health monitoring, security, and surveillance generates non-stationary datastreams. Due to such nature, the statistical properties of data changes overtime, leading to class imbalance and concept drift issues. Both these issuescause model performance degradation. Most of the current work has beenfocused on developing an ensemble strategy by training a new classifier on thelatest data to resolve the issue. These techniques suffer while training the newclassifier if the data is imbalanced. Also, the class imbalance ratio may changegreatly from one input stream to another, making the problem more *** existing solutions proposed for addressing the combined issue of classimbalance and concept drift are lacking in understating of correlation of oneproblem with the other. This work studies the association between conceptdrift and class imbalance ratio and then demonstrates how changes in classimbalance ratio along with concept drift affect the classifier’s *** analyzed the effect of both the issues on minority and majority classesindividually. To do this, we conducted experiments on benchmark datasetsusing state-of-the-art classifiers especially designed for data stream ***, recall, F1 score, and geometric mean were used to measure theperformance. Our findings show that when both class imbalance and conceptdrift problems occur together the performance can decrease up to 15%. Ourresults also show that the increase in the imbalance ratio can cause a 10% to15% decrease in the precision scores of both minority and majority *** study findings may help in designing intelligent and adaptive solutionsthat can cope with the challenges of non-stationary data streams like conceptdrift and class imbalance.

关键词： Classification data streams class imbalance concept drift class imbalance ratio

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Deep Learning Based End-to-End Specular Reflection Removal for Medical Endoscopic Images 23

Deep Learning Based End-to-End Specular Reflection Removal f...

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2023 Research in Adaptive and Convergent Systems, RACS 2023

作者： Shih, Chi-Sheng Liao, Yu-Cheng Tan, Ching-Ting Graduate Institute of Networking and Multimedia Department of Computer Science and Information Engineering High Performance and Scientific Computing Center National Taiwan University Taipei Taiwan Graduate Institute of Networking and Multimedia National Taiwan University Taipei Taiwan Department of Otolaryngology National Taiwan University Hospital Taipei Taiwan

ISBN: (纸本)9798400702280

Endoscopic images usually have many overexposed regions due to strong and focused light sources and, consequently, physicians need to change the camera angle for a clear view from time to time. This work targets removing the specular reflections from the endoscopy images but maintaining the structural and semantic texture in the images. Unlike the state-of-the-art image inpainting methods, the proposed method treats the specular reflection removal problem as an image-to-image translation task by skipping the specular detection step. The technique uses Dense Multi-scale Fusion Network (DMFN), which aims for small size and clear images, as the base and revises the network to support the large size and noisy endoscopy images. Moreover, the method can recover structure from large overexposed regions. Experimental results show that under different glare ratios and granularity settings, it is more effective than the Partial Convolution Model when recovering the corrupted pixels: the mean average error of pixel values decreases 13.2%, and the PSNR value increases 2.62dB. Qualitative analysis shows that even in the worst case when the proposed model generates output images with MAE up to 4.30, its recoveries still possess good visual qualities. The proposed model can process a 480 × 768 image in 16.2ms on a computer equipped with 36 CPU cores and an RTX-3090 GPU. It usually takes at least 20 minutes for a human to recover such images. © 2023 ACM.

关键词： Endoscopy

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SNNPG: Using Spiking Neural Networks to Detect Attacks in the Power Grid

SNNPG: Using Spiking Neural Networks to Detect Attacks in th...

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Neuromorphic Systems (ICONS), International Conference on

作者： Kendric Hood Ang Li Qiang Guan Computer Science Department Kent State University Kent United States High-Performance Computing (HPC) group Pacific Northwest National Laboratory Richland United States

ISBN: (数字)9798350368659

ISBN: (纸本)9798350368666

We explore the potential of Spiking Neural Networks (SNN) to enhance the security of power grid operations by detecting False Data Injection (FDI) attacks. These attacks manipulate PMU readings, leading to erroneous control decisions and grid disruptions. We develop a method to convert Phase Measurement Unit (PMU) data into spike trains, capturing both temporal and spatial dimensions. Using an SNN model, we conduct evaluations with simulated power grid data, showcasing accuracy in detecting FDI attacks. SNN models rapidly identity anomalies in real-time PMU data, safeguarding grid operations by alerting operators to irregular readings and preventing incorrect decisions.

关键词： Accuracy Phase measurement Neuromorphics Computational modeling Spiking neural networks Power grids Phasor measurement units Data models Real-time systems Security

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Interacting plexcitons for designed ultrafast optical nonlinearity in a monolayer semiconductor

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Light(Science & Applications) 2022年第5期11卷 877-887页

作者： Yuxiang Tang Yanbin Zhang Qirui Liu Ke Wei Xiang’ai Cheng Lei Shi Tian Jiang College of Advanced Interdisciplinary Studies National University of Defense Technology410073 ChangshaChina Key Laboratory of Micro-and NanoPhotonic Structures(Ministry of Education) and State Key Laboratory of Surface PhysicsDepartment of PhysicsFudan University200433 ShanghaiChina State Key Laboratory of High Performance Computing College of ComputerNational University of Defense Technology410073 ChangshaChina Beijing Institute for Advanced Study National University of Defense Technology100000 BeijingChina

Searching for ideal materials with strong effective optical nonlinear responses is a long-term task enabling remarkable breakthroughs in contemporary quantum and nonlinear ***,hybridized light-matter quasiparticles,are an appealing candidate to realize such ***,we explore a class of peculiar polaritons,named plasmon–exciton polaritons(plexcitons),in a hybrid system composed of silver nanodisk arrays and monolayer tungsten-disulfide(WS2),which shows giant room-temperature nonlinearity due to their deep-subwavelength localized ***,comprehensive ultrafast pump–probe measurements reveal that plexciton nonlinearity is dominated by the saturation and higher-order excitation-induced dephasing interactions,rather than the well-known exchange interaction in traditional microcavity ***,we demonstrate this giant nonlinearity can be exploited to manipulate the ultrafast nonlinear absorption properties of the solid-state *** findings suggest that plexcitons are intrinsically strongly interacting,thereby pioneering new horizons for practical implementations such as energy-efficient ultrafast all-optical switching and information processing.

关键词： nonlinearity monolayer nonlinear

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Anomalous negative magnetoresistance in quantum dot Josephson junctions with Kondo correlations

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Science China(Physics,Mechanics & Astronomy) 2024年第8期67卷 3-13页

作者： Mingtang Deng Chunlin Yu Guangyao Huang Rosa López Philippe Caroff Sepideh Ghalamestani Gloria Platero Hongqi Xu Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China NanoLund and Division of Solid State Physics Lund UniversityLund S-22100Sweden China Greatwall Quantum Laboratory Changsha 410006China Institut de Física Interdisciplinària i de Sistemes Complexos IFISC Palma de Mallorca E-07122Spain Instituto de Ciencia de Materiales de Madrid Madrid 28049Spain Beijing Key Laboratory of Quantum Devices Key Laboratory for the Physics and Chemistry of Nanodevicesand Department of ElectronicsPeking UniversityBeijing 100871China Beijing Academy of Quantum Information Sciences Beijing 100193China Hefei National Laboratory Hefei 230088China

The interplay between superconductivity and the Kondo effect has stimulated significant interest in condensed matter *** compete when their critical temperatures are close and can give rise to a quantum phase transition that can mimic Majorana zero ***,we have fabricated and measured Al-InSb nanowire quantum dot-Al *** the Kondo regime,a supercurrent-induced zero-bias conductance peak *** zero-bias peak shows an anomalous negative magnetoresistance(NMR)at weak magnetic *** attribute this anomalous NMR to quasiparticle trapping at vortices in the superconductor leads as a weak magnetic field is *** trapping effect lowers the quasiparticle-caused dissipation and thus enhances the Josephson *** work connects the vortex physics and the supercurrent tunneling in Kondo regimes and can help further understand the physics of Josephson quantum dot system.

关键词： quantum dot Kondo correlation InSb nanowire quasiparticle trapping

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Valley Hall effect and kink states in topolectrical circuits

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Physical Review Research 2023年第1期5卷 013107-013107页

作者： S. M. Rafi-Ul-Islam Zhuo Bin Siu Haydar Sahin Mansoor B. A. Jalil Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Republic of Singapore Institute of High Performance Computing A*STAR Singapore 138632 Republic of Singapore

We investigate the emergence of topological valley Hall and kink states in a two-dimensional topolectrical (TE) model as a result of broken chiral and reflection symmetries. The TE system consists of two segments hosting distinct topological states with opposite (similar) signs of the valley Hall index, and separated by a heterojunction to exhibit valley kink (Chern insulating) phases at the interface. In the practical circuit, the valley Hall index can be flipped between the two segments by modulating the on-site potential on the sublattice nodes of the respective segments. The presence of grounding connections in the circuit array subsequently leads to the emergence of gapped and gapless valley and kink states in the admittance spectra. These topological modes can be detected electrically by the impedance readouts of the system, which can be correlated to its admittance spectra. Finally, we confirm the robustness of the valley Hall and kink states via realistic LTspice simulation, taking into account the tolerance windows and parasitic effects inherent in circuit components. Our study demonstrates the applicability of TE circuit networks as a platform to realize and tune valley-dependent and kink topological phenomena.

关键词： Topological insulators Topological phases of matter Valleytronics 2-dimensional systems Band structure methods Bloch wave theory Green's function methods Tight-binding model

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Disentangled latent factors for muti-cause treatment effect estimation 6

Disentangled latent factors for muti-cause treatment effect ...

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2024 6th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2024

作者： Zhao, Zhuoyue Wang, Haotian Xu, Liyang Wang, Qian Tang, Yuhua Department of Intelligent Data Science National University of Defense Technology Changsha410073 China Intelligent Game and Decision Lab. Academy of Military Science Beijing100071 China Institute for Quantum Information State Key Laboratory of High-Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China

Existing methods estimate treatment effects from observational data and assume that covariates are all confounders. However, observed covariates may not directly represent confounding variables that influence both treatment and outcome. They always include variables that only affect the treatment or the outcome. In addition, for multi-dimensional binary treatments, disentangled methods are mainly designed for binary variables and ignore the impact of multi-cause treatment variables on the inference of latent factors. To address these two issues, based on variable decomposition and proxy inference, we propose the Disentangled Latent Factors for Multi-cause Treatment Estimation (DEMTE) algorithm. It utilizes an identifiable autoencoder to infer and disentangle latent factors based on the joint distribution of variables in observational data. DEMTE evaluates the treatment effect on the disentangled factors. Synthetic experiments and semi-synthetic experiments demonstrate the effectiveness of the inference and disentanglement techniques and our method achieves more accurate treatment effect estimation. © 2024 Institute of Physics Publishing. All rights reserved.

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Development of a Training Framework for Novel Accelerators 53

Development of a Training Framework for Novel Accelerators

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： He, Zhenhua Nite, Sandra Winchell, Joshua Nasari, Abhinand Le, Hieu Tao, Jiao Chakravorty, Dhruva Perez, Lisa Liu, Honggao Texas A&m University High Performance Research Computing College StationTX United States Texas A&m University Department of Electrical and Computer Engineering College StationTX United States Texas A&m University Department of Visualization College StationTX United States

ISBN: (纸本)9798350336429

In recent years, accelerators such as Graphics Processing Units (GPUs), Field Programmable Gate Arrays (FPGAs), and Intelligence Processing Units (IPUs) have played a dominant role in speeding up workflows in science and engineering. They provide significant increases in computing power, but scientists need to learn how to effectively use these accelerators. To assist researchers, a training framework, called 'Technology Laboratories', was developed. The Technology Laboratories approach builds on situated learning and constructivism by introducing researchers to new computing concepts by scaffolding with existing knowledge of computing resources like GPUs and Jupyter Notebooks. In this approach, researchers are introduced to the newer computing methods by employing accelerators and interactive technologies familiar to them. The first iteration of the training framework was used to teach researchers how to use different methods of artificial intelligence and machine learning (AI/ML) through exercises built on familiar computing environments. New accelerator technologies like IPUs have focused on employing these AI/ML techniques, presenting an opportunity to now teach new computing accelerators using AI/ML models as the familiar computing method. Lave and Wenger's model of situated learning through a community of practice is appropriate for this learning. Additionally, Jerome Bruner's constructivist theory is part of the model as researchers are also required to construct their own knowledge about transforming their code and learning to adapt to a new type of hardware as they work through the individual characteristics of their code and research area. In this paper, we demonstrate the success of our training framework in using AI/ML methods to teach researchers about IPUs. We attracted interested participants from all over the United States, and they were able to complete hands-on exercises and run code on IPUs. We also had in-depth discussions with participants about

关键词： AI/ML Intelligence Processing Units Novel Accelerators Training Framework

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A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization 27

A First-Order Multi-Gradient Algorithm for Multi-Objective B...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Ye, Feiyang Lin, Baijiong Cao, Xiaofeng Zhang, Yu Tsang, Ivor W. Department of Computer Science and Engineering Southern University of Science and Technology China Australian Artificial Intelligence Institute University of Technology Sydney Australia The Hong Kong University of Science and Technology Guangzhou China School of Artificial Intelligence Jilin University China Shanghai Artificial Intelligence Laboratory China Centre for Frontier AI Research Agency for Science Technology and Research Singapore Institute of High Performance Computing Agency for Science Technology and Research Singapore School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781643685489

In this paper, we study the Multi-Objective Bi-Level Optimization (MOBLO) problem, where the upper-level subproblem is a multi-objective optimization problem and the lower-level subproblem is for scalar optimization. Existing gradient-based MOBLO algorithms need to compute the Hessian matrix, causing the computational inefficient problem. To address this, we propose an efficient first-order multi-gradient method for MOBLO, called FORUM. Specifically, we reformulate MOBLO problems as a constrained multi-objective optimization (MOO) problem via the value-function approach. Then we propose a novel multi-gradient aggregation method to solve the challenging constrained MOO problem. Theoretically, we provide the complexity analysis to show the efficiency of the proposed method and a non-asymptotic convergence result. Empirically, extensive experiments demonstrate the effectiveness and efficiency of the proposed FORUM method in different learning problems. In particular, it achieves state-of-the-art performance on three multi-task learning benchmark datasets. © 2024 The Authors.

关键词： Optimization algorithms

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Numerical simulations of attachment-line boundary layer in hypersonic flow, Part II: the features of three-dimensional turbulent boundary layer

arXiv

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arXiv 2024年

作者： Xi, Youcheng Yan, Bowen Yang, Guangwen Song, Fu School of Aerospace Engineering Tsinghua University Beijing100084 China Institute of High Performance Computing Department of Computer Science and Technology Tsinghua University Beijing100084 China

In this study, we investigate the characteristics of three-dimensional turbulent boundary layers influenced by transverse flow and pressure gradients. Our findings reveal that even without assuming an infinite sweep, a fully developed turbulent boundary layer over the present swept blunt body maintains spanwise homogeneity, consistent with infinite sweep assumptions. We critically examine the law-of-the and temperature-velocity relationships, typically applied two-dimensional turbulent boundary layers, in three-dimensional contexts. Results show that with transverse velocity and pressure gradient, streamwise velocity adheres to classical velocity transformation relationships and the predictive accuracy of classical temperature-velocity relationships diminishes because of pressure gradient. We show that near-wall streak structures persist and correspond with energetic structures in the outer region, though three-dimensional effects redistribute energy to align more with the external flow direction. Analysis of shear Reynolds stress and mean flow shear directions reveals in near-wall regions with low transverse flow velocity, but significant deviations at higher transverse velocities. Introduction of transverse pressure gradients together with the transverse velocities alter the velocity profile and mean flow shear directions, with shear Reynolds stress experiencing similar changes but with a lag increasing with transverse. Consistent directional alignment in outer regions suggests a partitioned relationship between shear Reynolds stress and mean flow shear: nonlinear in the inner region and approximately linear in the outer region. © 2024, CC BY.

关键词： Pressure gradient

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