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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Trabelsi, Mohamed Makhamreh, Hamza Alquennah, Alamera Nouran Vahedi, Hani Kuwait College of Science and Technology Electronics and Communications Engineering Department Kuwait City Kuwait Özyeǧin University Department of Electrical and Electronic Engineering Istanbul Turkey Texas A&m University Department of Electrical and Computer Engineering College StationTX77843 United States Texas A&m University at Qatar Qatar Foundation Doha Qatar Delft University of Technology Department of Electrical Engineering Mathematics and Computer Science Delft Netherlands

ISBN: (纸本)9798350331820

This study proposes the application of a Lyapunov-based Model Predictive Control (L-MPC) approach to a 9-level Crossover Switches Cell (CSC9) converter operating in grid connection mode. The proposed method utilizes the structure of the classical finite-control-set MPC (FCS-MPC) technique while integrating a cost function that requires no tuning. By deriving the cost function based on Lyapunov theory, the system stability is ensured. Notably, the suggested approach offers several advantages over traditional MPC controllers. Firstly, it eliminates the need for gain tuning, thereby simplifying the implementation process. Secondly, the proposed controller prioritizes stability as a key design aspect. The presented simulation results prove that the proposed controller effectively regulates the voltage of the DC capacitor around its desired value and feed a smooth sinusoidal current to the grid with low total harmonic distortion (THD) while operating at a unity power factor. © 2023 IEEE.

关键词： Controllers

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Rampo: A CEGAR-based Integration of Binary Code Analysis and System Falsification for Cyber-Kinetic Vulnerability Detection

Rampo: A CEGAR-based Integration of Binary Code Analysis and...

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IEEE/ACM International Conference on Cyber-Physical Systems (ICCPS)

作者： Kohei Tsujio Mohammad Abdullah Al Faruque Yasser Shoukry Department of Electrical Engineering and Computer Science University of California Irvine

ISBN: (数字)9798350369274

ISBN: (纸本)9798350369281

Cyber-physical systems (CPS) play a pivotal role in modern critical infrastructure, spanning sectors such as energy, transportation, healthcare, and manufacturing. These systems combine digital and physical elements, making them susceptible to a new class of threats known as cyber kinetic vulnerabilities. Such vulnerabilities can exploit weaknesses in the cyber world to force physical consequences and pose significant risks to both human safety and infrastructure integrity. This paper presents a novel tool, named Rampo, that can perform binary code analysis to identify cyber kinetic vulnerabilities in CPS. The proposed tool takes as input a Signal Temporal Logic (STL) formula that describes the kinetic effect—i.e., the behavior of the "physical" system—that one wants to avoid. The tool then searches the possible "cyber" trajectories in the binary code that may lead to such "physical" behavior. This search integrates binary code analysis tools and hybrid systems falsification tools using a Counter-Example Guided Abstraction Refinement (CEGAR) approach. In particular, Rampo starts by analyzing the binary code to extract symbolic constraints that represent the different paths in the code. These symbolic constraints are then passed to a Satisfiability Modulo Theories (SMT) solver to extract the range of control signals that can be produced by each of the paths in the code. The next step is to search over possible "physical" trajectories using a hybrid systems falsification tool that adheres to the behavior of the "cyber" paths and yet leads to violations of the STL formula. Since the number of "cyber" paths that need to be explored increases exponentially with the length of "physical" trajectories, we iteratively perform refinement of the "cyber" path constraints based on the previous falsification result and traverse the abstract path tree obtained from the control program to explore the search space of the system. To illustrate the practical utility of binary code ana

关键词： Numerical analysis Transportation Binary codes Medical services Cyber-physical systems Aerospace electronics Kinetic theory

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Multi-RIS Deployment for High Data-Rate Communications

Multi-RIS Deployment for High Data-Rate Communications

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2022 International Conference on Networking and Network Applications, NaNA 2022

作者： Khan, Muhammad Fawad Mei, Haoran Rahim, Shahnila Peng, Limei Ho, Pin-Han School of Computer Science and Engineering Kyungpook National University Deagu Korea Republic of University of Waterloo Department of Electrical and Computer Engineering WaterlooON Canada

ISBN: (数字)9781665461313

ISBN: (纸本)9781665461313

This paper proposes using multiple reconfigurable intelligent surfaces (RISs) in SISO communications, considering that RISs can flexibly extend the wireless communication range. In a given area with multiple RISs, we propose an algorithm to select the optimal locations from a set of candidate points to deploy the RISs, aiming to maximize the achievable data rate. We investigate the impact of single-hop and multi-hops communication on the achievable data rate for the proposed algorithm and the results show that the deployment height and number of communication hops significantly affect the achievable data rate. © 2022 IEEE.

关键词： Wireless communication Spread spectrum communication Reconfigurable intelligent surfaces SISO communication

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Efficient List-decoding of Polynomial Ideal Codes with Optimal List Size

arXiv

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arXiv 2024年

作者： Ron-Zewi, Noga Venkitesh, S. Wootters, Mary Department of Computer Science University of Haifa Departments of Computer Science Department of Electrical Engineering Stanford University United States

In a recent breakthrough [BGM23, GZ23, AGL23], it was shown that randomly punctured Reed-Solomon codes are list decodable with optimal list size with high probability, i.e., they attain the Singleton bound for list decoding [ST20, Rot22, GST22]. We extend this result to the family of polynomial ideal codes, a large class of error-correcting codes which includes several well-studied families of codes such as Reed-Solomon, folded Reed-Solomon, and multiplicity codes. More specifically, similarly to the Reed-Solomon setting, we show that randomly punctured polynomial ideal codes over an exponentially large alphabet exactly achieve the Singleton bound for list-decoding;while such codes over a polynomially large alphabet approximately achieve it. Combining our results with the efficient list-decoding algorithm for a large subclass of polynomial ideal codes of [BHKS21], implies as a corollary that a large subclass of polynomial ideal codes (over random evaluation points) is efficiently list decodable with optimal list size. To the best of our knowledge, this gives the first family of codes that can be efficiently list decoded with optimal list size (for all list sizes), as well as the first family of linear codes of rate R that can be efficiently list decoded up to a radius of 1 − R − ǫ with list size that is polynomial (and even linear) in 1/ǫ. Our result applies to natural families of codes with algebraic structure such as folded Reed-Solomon or multiplicity codes (over random evaluation points). Our proof follows the general framework of [BGM23, GZ23, AGL23], but several new ingredients are needed. The main two new ingredients are a polynomial-ideal GM-MDS theorem (extending the algebraic GM-MDS theorem of [YH19, Lov21]), as well as a duality theorem for polynomial ideal codes, both of which may be of independent interest. © 2024, CC BY.

关键词： Polynomials

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Transformers provably learn sparse token selection while fully-connected nets cannot 24

Transformers provably learn sparse token selection while ful...

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Proceedings of the 41st International Conference on Machine Learning

作者： Zixuan Wang Stanley Wei Daniel Hsu Jason D. Lee Department of Electrical and Computer Engineering Princeton University NJ Department of Computer Science Columbia University NY

The transformer architecture has prevailed in various deep learning settings due to its exceptional capabilities to select and compose structural information. Motivated by these capabilities, Sanford et al. (2023) proposed the sparse token selection task, in which transformers excel while fully-connected networks (FCNs) fail in the worst case. Building upon that, we strengthen the FCN lower bound to an average-case setting and establish an algorithmic separation of transformers over FCNs. Specifically, a one-layer transformer trained with gradient descent provably learns the sparse token selection task and, surprisingly, exhibits strong out-of-distribution length generalization. We provide empirical simulations to justify our theoretical findings.

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Support Vector Machines for Fault Detection and Classification in electrical Systems

Support Vector Machines for Fault Detection and Classificati...

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2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

作者： Goyal, Himanshu Rai Habelalmateen, Mohammed I. Badhoutiya, Arti Deepak, A. Pushkarna, Gaurav Harikrishna, M. Graphic Era Deemed To Be University Department Of Computer Science & Engineering Dehradun India College Of Technical Engineering The Islamic University Department Of Computers Techniques Engineering Najaf Iraq Gla University Department Of Electrical Engineering Mathura India Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Saveetha University Tamilnadu Chennai India Lovely Professional University Phagwara India Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India

ISBN: (纸本)9798350366846

The investigation examines the application of Support Vector Machines (SVMs) for blame location and classification in electrical frameworks, pointing to an upgrade of the reliability of critical foundations. Four SVM-based algorithms - Linear SVM (LSVM), Polynomial SVM (PSVM), Radial Basis Function SVM (RSVM), and Sigmoid SVM (SSVM) - were utilized and assessed for their viability in capturing differing blame scenarios. Among these, the RSVM show utilizing Radial Basis Function parts illustrated prevalent execution, accomplishing an accuracy of 96%, precision of 95%, recall of 97%, and an F1-score of 96%. The study contributes to the field by highlighting the versatility and strength of SVMs in tending to complex blame patterns within electrical frameworks. Comparisons with related work emphasize the predominance of the proposed SVM-based approach, outperforming modern strategies in terms of exactness, exactness, review, and F1 score. Also, the outline of related work emphasizes the broader scene of blame discovery strategies, exhibiting differing procedures such as Kernel Principal Component Analysis, Long Short-Term Memory Neural Networks, gathering learning, and edge computing. In conclusion, the research implies the noteworthiness of leveraging progressed machine learning strategies, especially SVMs, for proficient and accurate fault discovery and classification in electrical frameworks. The discoveries offer important experiences for professionals and analysts, giving an establishment for assist headways in blame location techniques and contributing to the proceeded improvement of electrical framework unwavering quality. © 2024 IEEE.

关键词： Support vector machines

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Delay-Guaranteed Path Selection and Scheduling in IAB Networks

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IEEE Transactions on Cognitive Communications and Networking 2024年

作者： Eftetahi, Pooria Seyed Cai, Lin Ren, Xiangyu Department of Electrical and Computer Engineering University of Victoria VictoriaBC Canada Department of Electrical & Computer Engineering the University of Victoria Canada Department of Automation Engineering University of Electronic Science and Technology of China Chengdu China

Integrated access and backhaul (IAB) is a promising solution to improve coverage at low deployment costs. In IAB networks, due to wireless channel variations, guaranteeing delay for delay-sensitive applications is a major challenge. Given the random traffic arrivals and channel variations, using a central controller for packet-level delay management becomes infeasible due to the added delay from the central controller. In this paper, we propose a distributed cross-layer method to provide delay-guaranteed path selection and scheduling for the IAB network where priority queues and weighted round robin are adopted to deliver differentiated services. Our goal is to determine the optimal path and scheduling decisions to maximize the total utility of the IAB network. We deploy an iterative approach in a distributed manner to solve the maximization problem at each IAB-node. Through simulation, we show that our proposed solution guarantees the delay at the packet-level while achieving considerable gains in terms of delay and packet delivery ratio compared to the state-of-the-art. © 2015 IEEE.

关键词： Delay-sensitive applications

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Differential Game Analysis of Energy Efficiency for Satellite Communication Subsystems 5

Differential Game Analysis of Energy Efficiency for Satellit...

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5th International Conference on Advances in Computational Tools for engineering Applications, ACTEA 2023

作者： Wan, Wei Cioffi, John M Peng, Yuanyuan Howard, Brenay S. Claflin University Department of Mathematics and Computer Science OrangeburgSC United States Stanford University Department of Electrical Engineering StanfordCA United States

ISBN: (纸本)9798350309959

A satellite transponder's communication channel is studied in this paper. The multiple terminal users in this channel compete for limited radio resources to satisfy their own data rate needs. Because inter-user interference limits the transponder's performance, it is beneficial for the transponder's power-control system to coordinate all users in its channel to reduce interference and to improve performance. By the special properties of channel gain in this type of channel, a non-cooperative Differential Game (DG) is set up to study the competition in a transponder's channel. Each user's utility is a trade-off between transmission data rate and power consumption. Nash Equilibrium (NE) is defined to be the solution of the DG model. The optimality condition of NE is derived to be a system of Differential Algebraic Equations (DAE). An algorithm based on minimizing all users' Hamiltonian is developed to solve the DAE system. The numerical solution of the NE provides the transponder's power control system with each user's power-control strategy at the equilibrium. © 2023 IEEE.

关键词： Energy efficiency

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Combining Financial Data and News Articles for Stock Price Movement Prediction Using Large Language Models

Combining Financial Data and News Articles for Stock Price M...

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IEEE International Conference on Big Data

作者： Ali Elahi Fatemeh Taghvaei Department of Computer Science University of Illinois Chicago Department of Electrical and Computer Engineering University of Illinois Chicago

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

Predicting financial markets and stock price movements requires analyzing a company’s performance, historic price movements, industry-specific events alongside the influence of human factors such as social media and press coverage. We assume that financial reports (such as income statements, balance sheets, and cash flow statements), historical price data, and recent news articles can collectively represent aforementioned *** combine financial data in tabular format with textual news articles and employ pre-trained Large Language Models (LLMs) to predict market movements. Recent research in LLMs has demonstrated that they are able to perform both tabular and text classification tasks, making them our primary model to classify the multi-modal data. We utilize retrieval augmentation techniques to retrieve and attach relevant chunks of news articles to financial metrics related to a company and prompt the LLMs in zero, two, and four-shot settings. Our dataset contains news articles collected from different sources, historic stock price, and financial report data for 20 companies with the highest trading volume across different industries in the stock market. We utilized recently released language models for our LLM-based classifier, including GPT- 3 and 4, and LLaMA- 2 and 3 *** introduce an LLM-based classifier capable of performing classification tasks using combination of tabular (structured) and textual (unstructured) data. By using this model, we predicted the movement of a given stock’s price in our dataset with a weighted F1-score of 58.5% and 59.1% and Matthews Correlation Coefficient of 0.175 for both 3-month and 6-month *** dataset and codes for this paper can be found on Github. https://***/aliielahi/FinedFMP 1

关键词： Measurement Presses Social networking (online) Large language models Text categorization Companies Predictive models Data models Stock markets Software development management

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High-Probability List-Recovery, and Applications to Heavy Hitters 49

High-Probability List-Recovery, and Applications to Heavy Hi...

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49th EATCS International Conference on Automata, Languages, and Programming, ICALP 2022

作者： Doron, Dean Wootters, Mary Department of Computer Science Ben-Gurion University of the Negev Beer-Sheva Israel Department of Computer Science and Electrical Engineering Stanford University CA United States

ISBN: (纸本)9783959772358

An error correcting code C: Σk → Σn is efficiently list-recoverable from input list size if for any sets L1,..., Ln ⊆ Σ of size at most , one can efficiently recover the list L = {x ∈ Σk : ∀j ∈ [n], C(x)j ∈ Lj}. While list-recovery has been well-studied in error correcting codes, all known constructions with "efficient" algorithms are not efficient in the parameter . In this work, motivated by applications in algorithm design and pseudorandomness, we study list-recovery with the goal of obtaining a good dependence on . We make a step towards this goal by obtaining it in the weaker case where we allow a randomized encoding map and a small failure probability, and where the input lists are derived from unions of codewords. As an application of our construction, we give a data structure for the heavy hitters problem in the strict turnstile model that, for some parameter regimes, obtains stronger guarantees than known constructions. © Dean Doron and Mary Wootters;licensed under Creative Commons License CC-BY 4.0

关键词： C (programming language)

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