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9th International Conference on Information Management, ICIM 2023

作者： Anand, M. Clement Joe Moorthy, C. Balakrishna Sivamani, S. Indrakumar, S. Kalaiarasi, K. Barhoi, Amir Department of Mathematics Karnataka Bengaluru India University of Technology & Applied Sciences Electrical Engineering Section Department of Engineering Salalah211 Oman Kongu Engineering College Department of Mathematics Tamil Nadu Erode India Department of Mathematics Tamil Nadu Tiruchirappalli India Duliajan College Department of Mathematics Assam India

ISBN: (纸本)9798350336382

In many areas, carbon cap-and-trade and carbon offsets are frequent and significant mechanisms for reducing carbon emissions. Furthermore, particular capital investments in green technologies can efficiently cut carbon emissions from corporate activities. However, such capital investments are expensive, and not all businesses/company can afford them. As a result, if all members of a supply chain agree to share facility investments, the supply chain can cut carbon emissions while also increasing profit. This study utilized crisp and fuzzy models to fix perishable products in the production process. The suggested model, for study is solved using python in machine learning. To cut carbon emissions and increase the total value of the supply chain system, we planned to integrate manufacturing, distribution, replenishment, and technology. Several cases are simulated, and the key parameters are subjected to sensitivity analysis. Under various carbon emission rules, the optimal solutions and joint total profit are also compared. Companies should be able to share risks by co-investing and building sustainable supply chains as a part of the future carbon emission control trend. © 2023 IEEE.

关键词： Python

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Constant-Loop Dominators for Single-Path Code Optimization 21

Constant-Loop Dominators for Single-Path Code Optimization

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21st International Workshop on Worst-Case Execution Time Analysis, WCET 2023

作者： Maroun, Emad Jacob Schoeberl, Martin Puschner, Peter Institute of Computer Engineering TU Wien Vienna Austria Department of Applied Mathematics and Computer Science Technical University of Denmark Lyngby Denmark

ISBN: (纸本)9783959772938

Single-path code is a code generation technique specifically designed for real-time systems. It guarantees that programs execute the same instruction sequence regardless of runtime conditions. Single-path code uses loop bounds to ensure all loops iterate a fixed number of times equal to their upper loop bound. When the lower and upper bounds are equal, the loop must iterate the same number of times, which we call a constant loop. In this paper, we present the constant-loop dominance relation on control-flow graphs. It is a variation of the traditional dominance relation that considers constant loops to find basic blocks that are always executed the same number of times. Using this relation, we present an optimization that reduces the code needed to manage single-path code. Our evaluation shows significant performance improvements, with one example of up to 90%, with mostly minor effects on code size. © Emad Jacob Maroun, Martin Schoeberl, and Peter Puschner.

关键词： Real time systems

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A Measurement based Predictive Maintenance Algorithm for Rigid-Body Dynamical Systems using Radial Basis Function Approximation and Information Theory 27

A Measurement based Predictive Maintenance Algorithm for Rig...

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27th International Conference on System Theory, Control and Computing, ICSTCC 2023

作者： Ortmann, Jan Ortmann, Mathis Department of Electrical Engineering and Computer Science University of Siegen Germany Department of Mathematics Justus Liebig University of Giessen Germany

ISBN: (纸本)9798350337983

This paper presents new viewpoints to solve predicative maintenance problems for arbitrarily rigid-body mechanical systems. Reliable predictions for changes in physical parameters are highly dependent on system model accuracy. Hence, costs for physical system modeling are expensive and time-consuming. To overcome this problem, we replaced the modeling process with a full measurement based procedure in conjunction with radial basis functions (RBF) approximation to create the system model. Subsequently, information theory is employed to generate a meaningful metric quantity that reports about the changes in physical parameters. A rigid-body mechanical system is used as an example to verify the presented theory. © 2023 IEEE.

关键词： Radial basis function networks

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New Delay Doppler Communication Paradigm in 6G Era:A Survey of Orthogonal Time Frequency Space(OTFS)

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China Communications 2023年第6期20卷 1-25页

作者： Weijie Yuan Shuangyang Li Zhiqiang Wei Yuanhao Cui Jiamo Jiang Haijun Zhang Pingzhi Fan Department of Electronic and Electrical Engineering Southern University of Science and TechnologyShenzhenChina Faculty of Electrical Engineering and Computer Science Technical University of BerlinBerlinGermany School of Mathematics and Statistics Xi’an Jiaotong UniversityXi’anChina Department of Communication Engineering Beijing University of Posts and TelecommunicationsBeijingChina China Academy of Information and Communications Technology BeijingChina School of Computer and Communication Engineering University of Science and Technology BeijingBeijingChina School of Information Science and Technology Southwest Jiaotong UniversityChengduChina

In the 6G era,Space-Air-Ground Integrated Network(SAGIN)are anticipated to deliver global coverage,necessitating support for a diverse array of emerging applications in high-mobility,hostile *** such conditions,conventional orthogonal frequency division multiplexing(OFDM)modulation,widely employed in cellular and Wi-Fi communication systems,experiences performance degradation due to significant Doppler *** overcome this obstacle,a novel twodimensional(2D)modulation approach,namely orthogonal time frequency space(OTFS),has emerged as a key enabler for future high-mobility use ***,OTFS modulates information within the delay-Doppler(DD)domain,as opposed to the timefrequency(TF)domain utilized by *** offers advantages such as Doppler and delay resilience,reduced signaling latency,a lower peak-to-average ratio(PAPR),and a reduced-complexity *** studies further indicate that the direct interplay between information and the physical world in the DD domain positions OTFS as a promising waveform for achieving integrated sensing and communications(ISAC).In this article,we present an in-depth review of OTFS technology in the context of the 6G era,encompassing fundamentals,recent advancements,and future *** objective is to provide a helpful resource for researchers engaged in the field of OTFS.

关键词： OTFS 6G delay-Doppler(DD)domain

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Towards new realities: Implications of personalized online layers in our daily lives

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i-com 2024年第2期23卷 221-229页

作者： Herder, Eelco Stojko, Laura Strecker, Jannis Neumayr, Thomas Yigitbas, Enes Augstein, Mirjam Department of Information and Computing Sciences Utrecht University Utrecht Netherlands Department of Computer Science University of the Bundeswehr Munich Neubiberg Germany Institute of Computer Science University of St. Gallen St. Gallen Switzerland Research Group Personalized Environments and Collaborative Systems University of Applied Sciences Upper Austria Hagenberg Austria Faculty of Electrical Engineering Computer Science and Mathematics Paderborn University Paderborn Germany

We are currently in a period of upheaval, as many new technologies are emerging that open up new possibilities to shape our everyday lives. Particularly, within the field of Personalized Human-computer Interaction we observe high potential, but also challenges. In this article, we explore how an increasing amount of online services and tools not only further facilitates our lives, but also shapes our lives and how we perceive our environments. For this purpose, we adopt the metaphor of personalized 'online layers' and show how these layers are and will be interwoven with the lives that we live in the 'human layer' of the real world. © 2024 the author(s), published by De Gruyter, Berlin/Boston.

关键词： Human computer interaction

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Multiview Orthonormalized Partial Least Squares: Regularizations and Deep Extensions

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IEEE Transactions on Neural Networks and Learning Systems 2023年第8期34卷 4371-4385页

作者： Wang, Li Li, Ren-Cang Lin, Wen-Wei The University of Texas at Arlington Department of Mathematics ArlingtonTX76019 United States The University of Texas at Arlington Department of Computer Science and Engineering ArlingtonTX76019 United States National Chiao Tung University Department of Applied Mathematics Hsinchu300 Taiwan

In this article, we establish a family of subspace-based learning methods for multiview learning using least squares as the fundamental basis. Specifically, we propose a novel unified multiview learning framework called multiview orthonormalized partial least squares (MvOPLSs) to learn a classifier over a common latent space shared by all views. The regularization technique is further leveraged to unleash the power of the proposed framework by providing three types of regularizers on its basic ingredients, including model parameters, decision values, and latent projected points. With a set of regularizers derived from various priors, we not only recast most existing multiview learning methods into the proposed framework with properly chosen regularizers but also propose two novel models. To further improve the performance of the proposed framework, we propose to learn nonlinear transformations parameterized by deep networks. Extensive experiments are conducted on multiview datasets in terms of both feature extraction and cross-modal retrieval. Results show that the subspace-based learning for a common latent space is effective and its nonlinear extension can further boost performance, and more importantly, one of two proposed methods with nonlinear extension can achieve better results than all compared methods. © 2012 IEEE.

关键词： Mathematical transformations

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Nonlinearity Estimation and Compensation for Accurate PMSM Modeling and Voltage Prediction

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CES Transactions on electrical Machines and Systems 2024年第4期8卷 394-403页

作者： Beichen Ding Yuting Lu Chunyan Lai Weiwen Peng Kaide Huang Guodong Feng IEEE School of Advanced Manufacturing Sun Yat-sen UniversityShenzhen 510275China School of Intelligent Systems Engineering Sun Yat-sen UniversityShenzhen 510275China Department of Electrical and Computer Engineering Concordia UniversityMontrealCanada School of Mathematics and Big Data Foshan UniversityFoshan 528000China

For permanent magnet synchronous machine(PMSM),the machine model is critical to predict the operating states for motor control,which,however,can be greatly affected by system ***,this paper investigates accurate machine modeling for control and parameter *** the proposed approach,the PMSM model with saturated inductances is used as the base model,and this paper investigates modeling and compensation of the offsets to the base model due to system nonlinearities such as saturation and core loss effects for accurate machine modeling and voltage ***,the offsets to the base model are modeled using nonlinear functions with variable coefficients to compensate saturation and core loss effect,which can achieve better accuracy without changing the model structure.A differential estimation model is derived to estimate the model coefficients from a small amount of measurements with simplified ***,the model offset calculation is both computation and memory efficient with simplified *** contribution is to improve the machine model accuracy and achieve precise voltage prediction for practical ***,comparisons and the application to temperature estimation are conducted on a test interior PMSM to validate the proposed approach.

关键词： Core loss Differential modeling Multiparameter estimation PMSM

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On the Online Weighted Non-Crossing Matching Problem 19

On the Online Weighted Non-Crossing Matching Problem

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19th Scandinavian Symposium on Algorithm Theory, SWAT 2024

作者： Boyar, Joan Kamali, Shahin Larsen, Kim S. Lavasani, Ali Mohammad Li, Yaqiao Pankratov, Denis Department of Mathematics and Computer Science University of Southern Denmark Odense Denmark Department of Electrical Engineering and Computer Science York University Toronto Canada Department of CSSE Concordia University Montreal Canada

ISBN: (纸本)9783959773188

We introduce and study the weighted version of an online matching problem in the Euclidean plane with non-crossing constraints: 2n points with non-negative weights arrive online, and an algorithm can match an arriving point to one of the unmatched previously arrived points. In the vanilla model, the decision on how to match (if at all) a newly arriving point is irrevocable. The goal is to maximize the total weight of matched points under the constraint that straight-line segments corresponding to the edges of the matching do not intersect. The unweighted version of the problem was introduced in the offline setting by Atallah in 1985, and this problem became a subject of study in the online setting with and without advice in several recent papers. We observe that deterministic online algorithms cannot guarantee a non-trivial competitive ratio for the weighted problem. We study various regimes of the problem which permit non-trivial online algorithms. In particular, when weights are restricted to the interval [1, U] we give a deterministic algorithm achieving competitive ratio Ω ( 2−2√logU). We also prove that deterministic online algorithms cannot achieve competitive ratio better than O ( 2−√logU) . Interestingly, we establish that randomization alone suffices to achieve competitive ratio 1/3 even when there are no restrictions on the weights. Additionally, if one allows an online algorithm to revoke acceptances, then one can achieve a competitive ratio ≈ 0.2862 deterministically for arbitrary weights. We also establish a lower bound on the competitive ratio of randomized algorithms in the unweighted setting, and improve the best-known bound on advice complexity to achieve a perfect matching. © Joan Boyar, Shahin Kamali, Kim S. Larsen, Ali Mohammad Lavasani, Yaqiao Li, and Denis Pankratov.

关键词： Geometry

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Integral Reinforcement Learning Control for a Class of Unknown Nonlinear Systems with an Application to a Microgrid System

Integral Reinforcement Learning Control for a Class of Unkno...

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2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

作者： Xu, Shanyong Su, Hanguang Liang, Xiaodong Yang, Jinzhu Wang, Jiawei Luan, Xinyang Northeastern University College of Information Science and Engineering Shenyang China University of Saskatchewan Department of Electrical and Computer Engineering Saskatoon Canada Northeastern University School of Computer Science and Engineering Shenyang China Northumbria University Department of Mathematics Physics and Electrical Engineering Newcastle United Kingdom

ISBN: (纸本)9781665471640

In this paper, a brand-new technique based on integral reinforcement learning (IRL) combined with the event-triggered control (ETC) for multiplayer non-zero-sum (NZS) game is proposed, taking into account nonlinear systems with uncertain system drift dynamics. System drift dynamics are no longer necessary for controller design with the IRL method. Furthermore, this method is implemented online, in contrast to other iterative calculating techniques. In this instance, the NZS game problems can be resolved by combining the IRL algorithm and the event-triggered control architecture. It offers a new triggering condition and lessens the computational and communication overhead of the entire control process. The system's stability is ensured at the same time. An example is then given to show how well our method works. © 2023 IEEE.

关键词： continuous-time system integral reinforcement learning (IRL) non-zero-sum (NZS) the event-triggered control (ETC) unknown dynamic

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A Textual Sentiment Analysis for Stock Price Volatility Forecasting using Bidirectional Long Short-Term Memory 1

A Textual Sentiment Analysis for Stock Price Volatility Fore...

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1st International Conference on Software, Systems and Information Technology, SSITCON 2024

作者： Kamma, Vidya Prasad, B. Ramyasri, Areman Shnain, Ammar H. Monisha Jothi, R. Neil Gogte Institute of Technology Department of Computer Science and Engineering Rangareddy Hyderabad India Sona College of Technology Department of Electrical and Electronics Engineering Salem India Department of Humanities and Mathematics Hyderabad India The Islamic University Department of Computers Techniques Engineering College of Technical Engineering Najaf Iraq New Prince Shri Bhavani College of Engineering and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350352931

A stock market is a place where business stocks and economic tools are bought and sold. It is a system of allstock transactions where stockholders and dealers purchase and retail shares. Moreover, a stock price prediction is a common problem for investors and stakeholders;so, they remain uncooperative in coming forward for market stocks. This study proposes a Bidirectional Long Short-Term Memory (Bi-LSTM) model to address the existing limitations of stock prediction. Initially, the data from Yahoo Finance is fed as input for preprocessing using a Kalman Filter (KF) that processes the data and reduces noise by dividing KF into prediction and update. Then, the preprocessed data is given as input for the transformer-XLNet, which integrates auto-encoding language into forward and backward directions. Later, the data is fed into textual sentiment analysis using Naϊve Bayes (NB) techniques. Finally, the output of the NB is fed as input to the Bi-LSTM prediction, which predicts the following-day finishing stock price based on the present-day concluding amount. Thus, BiLSTM resulted in greater efficiency when compared with the existing methods like Neutrosophic Logic Sentiment Analysis (NL-SA) in terms of accuracy (97.87%), sensitivity (89.90%), f1-score (91.12%), specificity (97.90%), andMCC (20.09%) respectively. © 2024 IEEE.

关键词： Kalman filters

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