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Artificial Intelligence and Signal Processing (AISP), INDIA, International Conference on

作者： Rohit Moningi Shreya Mahakur Shradha Mundada Asis Kumar Tripathy School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (数字)9798350350654

ISBN: (纸本)9798350350661

The ECG is fundamental in detecting cardiovascular ailments, and its thorough analysis is imperative. The analysis of conventional ECG depends on interpretation based on the expertise of the professional, which is slow and prone to mistakes. Deep learning models, which include CNNs, LSTMs, and Attention techniques introduced recently, have demonstrated promising results in the automation of ECG classification with high accuracy. However, a major drawback regarding these models is the ‘black box’ nature, which goes against clinical usage and comparison. This study adopts SHapley Additive exPlanations (SHAP) values and Local Interpretable Model-agnostic Explanations (LIME) techniques under deep learning algorithms for identifying ECG heartbeats. The model is trained and tested on the MIT-BIH Arrhythmia Database, and the performance seems to be accurate with an overall accuracy of 98.25%. Local Interpretable Model-Agnostic Explanations involving the construction of a local model, such as LIME and Shapely Additive explanations, or SHAP, help to provide more explanation regarding what the model is doing, thus increasing its reliability for clinical use. In this paper, the focus is presented on the experiment's method and outcomes, with a discussion of the interpretability of the final model as a crucial factor in its application in medical diagnostics.

关键词： Deep learning Accuracy Additives Heart beat Signal processing algorithms Electrocardiography Signal processing Reliability Medical diagnosis Artificial intelligence

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WISER: Weak Supervision and Supervised Representation Learning to Improve Drug Response Prediction in Cancer 41

WISER: Weak Supervision and Supervised Representation Learni...

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41st International Conference on Machine Learning, ICML 2024

作者： Shubham, Kumar Jayagopal, Aishwarya Danish, Syed Mohammed Prathosh, A.P. Rajan, Vaibhav Department of Electrical Communication Engineering Indian Institute of Science Karnataka Bengaluru India Department of Information Systems and Analytics School of Computing National University of Singapore Singapore Indian Institute of Technology Bihar Patna India

Cancer, a leading cause of death globally, occurs due to genomic changes and manifests heterogeneously across patients. To advance research on personalized treatment strategies, the effectiveness of various drugs on cells derived from cancers (‘cell lines') is experimentally determined in laboratory settings. Nevertheless, variations in the distribution of genomic data and drug responses between cell lines and humans arise due to biological and environmental differences. Moreover, while genomic profiles of many cancer patients are readily available, the scarcity of corresponding drug response data limits the ability to train machine learning models that can predict drug response in patients effectively. Recent cancer drug response prediction methods have largely followed the paradigm of unsupervised domain-invariant representation learning followed by a downstream drug response classification step. Introducing supervision in both stages is challenging due to heterogeneous patient response to drugs and limited drug response data. This paper addresses these challenges through a novel representation learning method in the first phase and weak supervision in the second. Experimental results on real patient data demonstrate the efficacy of our method WISER (Weak supervISion and supErvised Representation learning) over state-of-the-art alternatives on predicting personalized drug response. Our implementation is available at https://***/kyrs/WISER. Copyright 2024 by the author(s)

关键词： Self-supervised learning

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Insights into the microstructural design of high-performance Ti alloys for laser powder bed fusion by tailoring columnar prior-βgrains andα-Ti morphology

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Journal of Materials science & technology 2024年第20期187卷 156-168页

作者： S.X.Wang S.F.Li X.M.Gan R.D.K.Misra R.Zheng K.Kondoh Y.F.Yang State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Science and Technology on Particle Materials Chinese Academy of SciencesBeijing 100190China Department of Metallurgical Materials and Biomedical EngineeringUniversity of TexasEl Paso TX 79968USA Joining and Welding Research Institution Osaka University11-1 MihogaokaIbarakiOsaka 567-0047Japan

A high-performance Ti-Ni-B alloy with good tensile properties and reduced mechanical anisotropy was developed by promoting the columnar to equiaxed transition(CET)of prior-βgrains and modifyingα-laths to equiaxed *** Ni and B contributed to the refinement of columnar prior-βgrains during the L→βphase transformation by generating constitutional *** with Ni,B had a su-perior capability of generating constitutional undercooling,which not only replaced a significant amount of Ni with a minor addition to reduce the formation of brittle eutectoid,but also reacted with Ti to form TiB to promote heterogeneous nucleation ofα-Ti grains during theβ→αphase *** with the restricted growth ofα-laths induced by the refinement of prior-βgrains,a fully equiaxedα-Ti structure was *** competition between the negative effect of brittle eutectoid and the positive role ofα-lath to equiaxed grain transition on the ductility of as-printed Ti-Ni-B alloys was fundamen-tally governed by the morphology of eutectoid and technically dependent on the Ni-B *** the addition was 1.2Ni-0.06B(wt.%)or less,the positive effect ofα-lath on equiaxed grain transition can effectively mitigate the issue of reduced ductility caused by brittle *** contrast,at 1.8Ni-0.09B or greater,the negative effect of eutectoid *** insights into microstructural design obtained through the aforementioned approach were presented and discussed.

关键词： Laser powder bed fusion Titanium alloys Grain refinement Powder processing Anisotropy

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Nonequilibrium carrier and phonon dynamics in the ferrimagnetic semiconductor Mn3Si2Te6

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Physical Review B 2024年第17期109卷 174309-174309页

作者： Y. Yang X. T. Chen Z. L. Li J. B. Pan F. Jing S. S. Zhang X. B. Wang J. L. Luo Key Laboratory of Education Ministry for Laser and Infrared System Integration Technology Beijing National Laboratory for Condensed Matter Physics School of Information Science and Engineering

We investigate the ultrafast carrier and phonon dynamics in the ferrimagnetic semiconductor Mn3Si2Te6 using time-resolved optical pump-probe spectroscopy. Our results reveal that the electron-phonon thermalization process with a subpicosecond timescale is prolonged by the hot-phonon bottleneck effect. We identify the subsequent relaxation processes associated with two nonradiative recombination mechanisms, i.e., phonon-assisted electron-hole recombination and defect-related Shockley-Read-Hall recombination. Temperature-dependent measurements indicate that all three relaxation components show large variation around 175 and 78 K, which is related to the initiation of spin fluctuation and ferrimagnetic order in Mn3Si2Te6. In addition, two pronounced coherent optical phonons are observed, in which the phonon with a frequency of 3.7 THz is attributed to the A1g mode of Te precipitates. Applying the strain pulse propagation model to the coherent acoustic phonons yields a penetration depth of 506 nm and a sound speed of 2.42 km/s in Mn3Si2Te6. Our results develop understanding of the nonequilibrium properties of the ferrimagnetic semiconductor Mn3Si2Te6 and also shed light on its potential applications in optoelectronic and spintronic devices.

关键词： Electron-phonon coupling Ferrimagnets Ultrafast femtosecond pump probe

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On a novel tracking differentiator design based on iterative learning in a moving window

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Control Theory and technology 2023年第1期21卷 46-55页

作者： Xiangyang Li Rafal Madonski Zhiqiang Gao Senping Tian Key Laboratory of Autonomous Systems and Network Control Ministry of EducationSchool of Automation Science and EngineeringSouth China University of TechnologyGuangzhou 510641China Energy and Electricity Research Center Jinan UniversityZhuhai 519070China Department of Electrical and Computer Science Cleveland State UniversityClevelandOH 44115USA

Differential signals are key in control engineering as they anticipate future behavior of process variables and therefore are critical in formulating control laws such as proportional-integral-derivative(PID).The practical challenge,however,is to extract such signals from noisy measurements and this difficulty is addressed first by *** in the form of linear and nonlinear tracking differentiator(TD).While improvements were made,TD did not completely resolve the conflict between the noise sensitivity and the accuracy and timeliness of the *** two approaches proposed in this paper start with the basic linear TD,but apply iterative learning mechanism to the historical data in a moving window(MW),to form two new iterative learning tracking differentiators(IL-TD):one is a parallel IL-TD using an iterative ladder network structure which is implementable in analog circuits;the other a serial IL-TD which is implementable digitally on any computer *** algorithms are validated in simulations which show that the proposed two IL-TDs have better tracking differentiation and de-noise performance compared to the existing linear TD.

关键词： Tracking differentiator(TD) Iterative learning Iterative learning tracking differentiator(IL-TD) Active disturbance rejection control(ADRC)-Two-dimensional system(2-D system)

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Model-Free Reinforcement Learning Economic Dispatch Algorithms for Price-Based Residential Demand Response Management System

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical systems 2023年 1卷 123-135页

作者： Li, Jun Li, Huaqing Huang, Tingwen Zheng, Lifeng Ji, Lianghao Yin, Shen Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China Texas A&M University at Qatar Doha Qatar Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications Chongqing400065 China Department of Mechanical and Industrial Engineering Faculty of Engineering Norwegian University of Science and Technology Trondheim7033 Norway

It is projected that plug-in electric vehicles (PEVs) would steadily increase as household appliances. However, PEVs’ high power consumption, stochastic usage patterns, and storage capacity will surely result in a rise in the elasticity of demand response and pose significant difficulties for price-based residential demand response management (PRDRM). This artcle aims to optimize a two-tier globally shared nonconvex PRDRM problem with local constraints and PEVs, known as social welfare: maximizing retailer profits and minimizing the combined residential costs. This is done by balancing residential electricity use with retail electricity prices in an unknown market environment. The proposed online/offline model-free reinforcement learning-based economic dispatch (MFRL-ED) methods can adaptively decide on the ideal retail price sequence by integrating the daily residential-retailer behavior model with the agent-environment interaction method, providing a basic MFRL-ED solution for PRDRM without a system identification step and an accurate load-retail model. Experiments show that MFRL-ED methods provide an effective class of PRDRM solutions. © 2023 Institute of Electrical and Electronics Engineers. All rights reserved.

关键词： Reinforcement learning

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Preface to Special Issue on Optoelectronic Neuromorphic Devices

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Journal of Semiconductors 2025年第2期46卷 2-4页

作者： Zhenyi Ni Zhongqiang Wang Jia Huang Xiaodong Pi State key Laboratory of Silicon and Advanced Semiconductor Materials&School of Materials Science and Engineering Zhejiang UniversityHangzhou 310027China Shangyu Institute of Semiconductor Materials Shaoxing 312300China Key Laboratory of UV-Emitting Materials and Technology of Ministry of Education Northeast Normal UniversityChangchun 130024China School of Materials Science and Engineering&National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji UniversityShanghai 201804China Institute of Advanced Semiconductors&Zhejiang Provincial Key Laboratory of Power Semiconductor Materials and Devices ZJ-UHangzhou Global Scientific and Technological Innovation CenterZhejiang UniversityHangzhou 311200China

The rapid advancement of artificial intelligence(AI),recognized with Nobel Prizes in both Physics and Chemistry in 2024,has been revolutionizing countless aspects of modern life,driving innovations across diverse fields and reshaping how people interact with *** its great advances,the computing of AI systems is now approaching the limit of traditional computing based on the von Neumann architecture,which is characterized by separated memory and process units-a challenge known as the"von Neumann bottleneck".

关键词： approaching separated Neumann

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Enhancing Alzheimer’s Disease Detection with Chaotic Moth Flame Optimization Algorithm: A Feature Selection Approach

Enhancing Alzheimer’s Disease Detection with Chaotic Moth F...

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Emerging Technologies in Computer science for Interdisciplinary Applications (ICETCS), International Conference on

作者： S Sabari Vasan P Jayalakshmi School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (数字)9798350372502

ISBN: (纸本)9798350372519

Advances in medical science have led to a better understanding of Alzheimer’s disease (AD), as shown by the clear description of AD using numerical, medical & MRI architectural imagery details. Early diagnosis of AD is possible using clinical data in addition its presence can be identified with huge correctness. Still, managing the massive and broadening AD data record is seemly an issue and utilising the unrefined data record unless removing redundant and duplicate data can significantly impact prediction or classification accuracy. Therefore, this research proposes an improved memetic metaheuristic behavioural founded feature selection framework called chaotic moth flame optimization algorithm (CMFOA). The suggested framework of MFO incorporates chaotic mapping to boost the search process, distinguishing it from the traditional form. CMFOA outperforms Ant colony optimization (ACO) and Firefly algorithm (FFA) in terms of ease, variable reduction, optimal efficiency, quick implementation, and rapid computing, resulting in improved subsets of characteristics for AD prediction. The study utilized the Alzheimer’s disease neuroimaging initiative (ADNI) dataset to ascertain potential characteristics implicated in the diagnosis of Alzheimer’s disease. The performance of the three feature subset selection approaches was validated using a deep neural network (DNN).The results demonstrated that CMFOA outperformed the other models in terms of accuracy.

关键词： Memetics Metaheuristics Fires Artificial neural networks Prediction algorithms Feature extraction Classification algorithms

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Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1262-1272页

作者： Mingming Ha Ding Wang Derong Liu School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Faculty of Information Technology the Beijing Key Laboratory of Computational Intelligence and Intelligent Systemthe Beijing Laboratory of Smart Environmental Protectionand the Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA IEEE

The core task of tracking control is to make the controlled plant track a desired *** traditional performance index used in previous studies cannot eliminate completely the tracking error as the number of time steps *** this paper,a new cost function is introduced to develop the value-iteration-based adaptive critic framework to solve the tracking control *** the regulator problem,the iterative value function of tracking control problem cannot be regarded as a Lyapunov function.A novel stability analysis method is developed to guarantee that the tracking error converges to *** discounted iterative scheme under the new cost function for the special case of linear systems is ***,the tracking performance of the present scheme is demonstrated by numerical results and compared with those of the traditional approaches.

关键词： Adaptive critic design adaptive dynamic programming(ADP) approximate dynamic programming discrete-time nonlinear systems reinforcement learning stability analysis tracking control value iteration(VI)

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Smart Contract-Based Advanced Financial Security System: A Literature Review

Smart Contract-Based Advanced Financial Security System: A L...

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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Prabanand, S.C. Thanabal, M.S. Mahalakshmi, P. Solairaj, A. Durai Murugan, A. Gowsika Sree, S.M. Department of Artificial Intelligence and Data Science Bannari Amman Institute of Technology Tamil Nadu Sathyamanagalam India Department of Computer Science and Engineering PSNA College of Engineering and Technology Tamil Nadu Dindigul India Department of Information Technology Kamaraj College of Engineering and Technology Tamil Nadu Virudhunagar India Department of Computer Science and Engineering Nadar Saraswathi College of Engineering and Technology Tamil Nadu Theni India Department of Computer Science and Business Systems M Kumarasamy College of Engineering Tamil Nadu Karur India

ISBN: (纸本)9798350305708

The current research provides a literature evaluation of works from sources such as IEEE and science Direct that explore testing and analysis methodologies and approaches for smart contracts. Smart contracts built on the blockchain have attracted a lot of attention from academics because of their unique properties. These include the immutability of transaction records, the automatic execution of contract instructions, and the decentralized building of trust. No one can deny blockchain's revolutionary potential across a number of sectors, but there are still technological hurdles to overcome before smart contracts gain widespread use. Solutions to these problems, as well as investigations into potential new uses for smart contracts outside of their present financial and logistics-related contexts, should guide future research efforts. In general, smart contracts built on blockchain technology have the power to revolutionize a number of sectors and open the door to a future that is more decentralized. © 2023 IEEE.

关键词： Blockchain concurrency Ethereum IoT scalability security smart contracts

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