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arXiv 2025年

作者： Zare, Hadi Abbasi, Mostafa Ahang, Maryam Najjaran, Homayoun Department of Electrical and Computer Engineering Faculty of Engineering and Computer Science University of Victoria Victoria Canada Department of Mechanical Engineering Faculty of Engineering and Computer Science University of Victoria Victoria Canada

Purpose - In Business Process Management (BPM), accurate prediction of the next activities is vital for operational efficiency and decision-making. Current Artificial Intelligence (AI)/Machine Learning (ML) models struggle with the complexity and evolving nature of business process event logs, balancing accuracy and interpretability. This paper proposes an entropy-driven model selection approach and DAW-Transformer, which stands for Dynamic Attribute-Aware Transformer, to integrate all attributes with a dynamic window for better accuracy. Design/methodology/approach - This paper introduces a novel next-activity prediction approach that uses process entropy to assess the complexity of event logs and dynamically select the most suitable ML model. A new transformer-based architecture with multi-head attention and dynamic windowing mechanism, DAW-Transformer, is proposed to capture long-range dependencies and utilize all relevant event log attributes. Experiments were conducted on six public datasets, and the performance was evaluated with process entropy. Finding - The results demonstrate the effectiveness of the approach across these publicly available datasets. DAW-Transformer achieved superior performance, especially on high-entropy datasets such as Sepsis exceeding Limited window Multi-Transformers by 4.69% and a benchmark CNN-LSTM-SAtt model by 3.07%. For low-entropy datasets like Road Traffic Fine, simpler, more interpretable algorithms like Random Forest performed nearly as well as the more complex DAW-Transformer and offered better handling of imbalanced data and improved explainability. Originality/ value - This work’s novelty lies in the proposed DAW-Transformer, with a dynamic window and considering all relevant attributes. Also, entropy-driven selection methods offer a robust, accurate, and interpretable solution for next-activity prediction. © 2025, CC BY-NC-SA.

关键词： Administrative data processing

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Multiscale aggregation and illumination-aware attention network for infrared and visible image fusion

Multiscale aggregation and illumination-aware attention netw...

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作者： Song, Wenhao Zhai, Wenzhe Gao, Mingliang Li, Qilei Chehri, Abdellah Jeon, Gwanggil School of Electrical and Electronic Engineering Shandong University of Technology Zibo China School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Department of Mathematics and Computer Science Royal Military College of Canada Kingston Canada Department of Embedded Systems Engineering Incheon National University Incheon Korea Republic of

Image fusion plays a significant role in computer vision since numerous applications benefit from the fusion results. The existing image fusion methods are incapable of perceiving the most discriminative regions under varying illumination circumstances and thus fail to emphasize the salient targets and ignore the abundant texture details of the infrared and visible images. To address this problem, a multiscale aggregation and illumination-aware attention network (MAIANet) is proposed for infrared and visible image fusion. Specifically, the MAIANet consists of four modules, namely multiscale feature extraction module, lightweight channel attention module, image reconstruction module, and illumination-aware module. The multiscale feature extraction module attempts to extract multiscale features in the images. The role of the lightweight channel attention module is to assign different weights to each channel so as to focus on the essential regions in the infrared and visible images. An illumination-aware module is employed to assess the probability distribution regarding the illumination factor. Meanwhile, an illumination perception loss is formulated by the illumination probabilities to enable the proposed MAIANet to better adjust to the changes in illumination. Experimental results on three datasets, that is, MSRS, TNO, and RoadSence, verify the effectiveness of the MAIANet in both qualitative and quantitative evaluations. © 2023 John Wiley & Sons, Ltd.

关键词： Image fusion

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A Novel Hybrid Tunicate Swarm Naked Mole-Rat Algorithm for Image Segmentation and Numerical Optimization

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computers, Materials & Continua 2022年第5期71卷 3445-3462页

作者： Supreet Singh Nitin Mittal Urvinder Singh Rohit Salgotra Atef Zaguia Dilbag Singh Department of Electronics&Communication Engineering Chandigarh UniversityMohali140413India Department of Electronics&Communication Engineering TIETPatiala147004India Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia School of Electrical Engineering and Computer Science Gwangju Institute of Science and TechnologyGwangju61005Korea

This paper provides a new optimization algorithm named as tunicate swarm naked mole-rat algorithm(TSNMRA)which uses hybridization concept of tunicate swarm algorithm(TSA)and naked mole-rat algorithm(NMRA).This newly developed algorithm uses the characteristics of both algorithms(TSA and NMRA)and enhance the exploration abilities of *** from the hybridization concept,important parameter of NMRA such as mating factor is made to be self-adaptive with the help of simulated annealing(sa)mutation operator and there is no need to define its value *** evaluating the working capabilities of proposed TSNMRA,it is tested for 100-digit challenge(CEC 2019)test problems and real multi-level image segmentation *** the results obtained for CEC 2019 test problems,it can be seen that proposed TSNMRA performs well as compared to original TSA and *** case of image segmentation problem,comparison of TSNMRA is performed with multi-threshold electro magnetism-like optimization(MTEMO),particle swarm optimization(PSO),genetic algorithm(GA),bacterial foraging(BF)and found superior results for TSNMRA.

关键词： Optimization NMRA TSA image segmentation thresholding

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Advanced Frequency Control for Renewable and Electric Vehicle Integrated Systems

Advanced Frequency Control for Renewable and Electric Vehicl...

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2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

作者： Pandit, Deepak Saket, Ram K. Cai, Niannian Nguyen, Nga University of Wyoming Electrical Engineering and Computer Science LaramieWY United States Department of Electrical Engineering Uttar Pradesh Varanasi India Google AustinTX United States

ISBN: (纸本)9798350331790

Modern power systems are experiencing a rapid movement from fossil-based generations to renewable energy resources (RERs) due to concerns about the environment and the dependence on fossil fuel sources. However, the replacement of conventional generation with intermittent and low inertia RERs in the power grid can negatively affect system regulation capability. Also, the increasing integration of electric vehicles (EVs) presents concerns over power system stability and reliability. To maintain the frequency of the system within stable limits, load frequency control (LFC) regulates the power output of the generating units in response to the changes in load demand. Therefore, appropriate control strategies and optimization algorithms are required for effective LFC while RER/EV penetration increases. In this paper, an advanced LFC model of a multi-area interconnected system with EV and RER integration is developed which considers the change in system inertia that arises from generator outages or the replacement of conventional units with RERs. A non-sequential Monte Carlo simulation (MCS) is implemented to calculate the system inertia and regulation capacity of each area considering the generator failure rates and load changes. The contribution of inertial response and primary frequency regulation from EVs to the system is assessed using a simulation-based approach. A particle swarm optimization (PSO) algorithm is used to tune the parameters of the PID controllers. The efficacy of the developed algorithm is demonstrated on a two-area model of the IEEE RTS-96 system with varying RER penetration levels. © 2023 IEEE.

关键词： Renewable energy resources

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Embedded Coded Relay System for Molecular Communications

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computers, Materials & Continua 2022年第8期72卷 2729-2748页

作者： Eman S.Attia Ashraf A.M.Khalaf Fathi E.Abd El-Samie Saied M.Abd El-atty Konstantinos A.Lizos Osama Alfarraj Farid Shawki Imran Khan Ki-Il Kim Department of Electrical Engineering Faculty of EngineeringMinia UniversityMiniaEgypt Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt Department of Informatics Faculty of Mathematics and Natural SciencesUniversity of Oslo(UiO)Norway Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Electrical Engineering University of Engineering&TechnologyPeshawar814Pakistan Department of Computer Science and Engineering Chungnam National UniversityDaejeon34134Korea

With the emergence of the COVID-19 pandemic,the World Health Organization(WHO)has urged scientists and industrialists to exploremodern information and communication technology(ICT)as a means to reduce or even eliminate *** World Health Organization recently reported that the virus may infect the organism through any organ in the living body,such as the respiratory,the immunity,the nervous,the digestive,or the cardiovascular *** the abovementioned goal,we envision an implanted nanosystem embedded in the intra living-body *** main function of the nanosystem is either to perform diagnosis and mitigation of infectious diseases or to implement a targeted drug delivery system(i.e.,delivery of the therapeutic drug to the diseased tissue or targeted cell).The communication among the nanomachines is accomplished via communication-based molecular *** control/interconnection of the nanosystem is accomplished through the utilization of Internet of bio-nano things(IoBNT).The proposed nanosystem is designed to employ a coded relay nanomachine disciplined by the decode and forward(DF)principle to ensure reliable drug delivery to the targeted ***,both the sensitivity of the drug dose and the phenomenon of drug molecules loss before delivery to the target cell site in long-distance due to the molecules diffusion process are taken into *** this paper,a coded relay NM with conventional coding techniques such as RS and Turbo codes is selected to achieve minimum bit error rate(BER)performance and high signal-to-noise ratio(SNR),while the detection process is based on maximum likelihood(ML)probability and minimum error probability(MEP).The performance analysis of the proposed scheme is evaluated in terms of channel capacity and bit error rate by varying system parameters such as relay position,number of released molecules,relay and receiver *** results are validated through simulation and demonstrate that the proposed scheme can

关键词： Molecular communication nanonetwork internet of bio-nano things coded relay scheme coding

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Characterization of All Optimal Finite-length Codes of Size Four for Binary Symmetric Channels

Characterization of All Optimal Finite-length Codes of Size ...

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2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Dong, Yanyan Yang, Shenghao National University of Singapore Department of Electrical and Computer Engineering Singapore The Chinese University of Hong Kong Shenzhen School of Science and Engineering Shenzhen China

ISBN: (纸本)9781665475549

The search for optimal finite-length binary block codes is a long-standing open problem for memoryless binary symmetric channels (BSCs) with the maximum likelihood decoding. A recent work studied the optimal codes among all binary codes of size four, including both linear codes and nonlinear codes, and showed the existence of optimal codes in the set composed of linear codes and Class-I codes for any given blocklength. Furthermore, for blocklength up to 300, it has been shown that there exists a linear code that is optimal among all the codes of size four. However, it is unknown whether there are optimal codes outside the set of linear codes and Class-I codes for a general blocklength. In this paper, we derive a subset of nonlinear codes called Class-II codes and justify that the set composed of linear, Class-I and Class-II codes and their equivalent codes includes all the optimal codes of size four when the blocklength is not equal to 3. For blocklength 3, we verify that there are nonlinear codes (not equivalent to linear, Class-I or Class-II codes) that are optimal. For the blocklength from 2 to 300 and not equal 3, our computer evaluations show that no nonlinear code is optimal except for the ones that are equivalent to linear codes. Moreover, we characterize all the best codes among all linear codes of size four for any given blocklength. © 2023 IEEE.

关键词： Optimal systems

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A Wide Voltage Gain Active Switched Inductor and Passive Switched Capacitor DC-DC Converter with Very Low Voltage Stress 3

A Wide Voltage Gain Active Switched Inductor and Passive Swi...

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3rd IEEE International Conference on Smart Technologies for Power, Energy and Control, STPEC 2023

作者： Kumar, Avneet Reza, Motiur Singh, Aakash Singh, Santosh K Behera, Ranjan Kumar Indian Institute of Technology Department of Electrical Engineering Patna India Khalifa University Department of Electrical Engineering and Computer Science Abu Dhabi United Arab Emirates Varanasi India

ISBN: (纸本)9798350304732

Severa1 applications such as Fuel Cell vehicle, HVDC system, aero-space industry require dc-dc converters having higher voltage gain. To provide optimum solution, a novel non-isolated, non-coupled inductor type dc-dc converters is proposed. The proposed dc-dc converter evolved by integrating active switched network and multiple switched capacitor network. Through this design, following features are achieved: high voltage gain, lower current stress on active switches, lower inductor current, lower voltage stress across devices and lower voltage stress across capacitors. The developed converter exhibits higher voltage gain along with lower voltage stress contrasted with other active switched inductor topologies. The operational and design analysis of the proposed converter is discussed and comparative analysis with the existing topologies are presented. A prototype of 200 W is developed in laboratory for boosting 20 V to 200 V and experimentation is carried out to verify the design. Additionally, the proposed converter is also tested under dynamic condition which illustrates the robustness of the converter with parameter variation. The reported maximum efficiency of the converter is found equal to 92.45%. © 2023 IEEE.

关键词： Switched Inductor Voltage Gain Voltage Stress

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Hierarchical Control for Cyber-Physical Systems via General Approximate Alternating Simulation Relations ⁎

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IFAC-PapersOnLine 2024年第11期58卷 13-18页

作者： Bingzhuo Zhong Murat Arcak Majid Zamani Department of Computer Science University of Colorado Boulder USA Department of Electrical Engineering and Computer Sciences University of California Berkeley USA

Traditional hierarchical control methodologies refine controllers from an abstract to a concrete system using a simulation relation established over the state sets of both systems. However, such a relation may yield a large error between the abstract and concrete systems, thus constraining the efficacy of hierarchical control architectures. To address this limitation, we introduce a more versatile simulation relation, namely general approximate alternating simulation relation, which also makes use of the input set of the abstract system. We demonstrate that our novel simulation relation effectively captures the similarity between the abstract and concrete system outperforming conventional simulation relations. Furthermore, it strengthens the hierarchical control architecture by reducing the error between the outputs of a concrete and its abstract system. We provide methods for establishing this new relation in linear control systems alongside their continuous abstractions. The practicality and effectiveness of our approach are underscored through its application in an illustrative example.

关键词： Simulation Relation Hierarchical Control Abstract System

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Physical-Design Aware Scan Cell Reordering for Low Power Testing

Physical-Design Aware Scan Cell Reordering for Low Power Tes...

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2024 IEEE East-West Design and Test Symposium, EWDTS 2024

作者： Badjatya, Rohit Vinay Kumar, Rahul Tudu, Jaynarayan T Fujita, Masahiro Singh, Virendra Indian Institute of Technology Bombay Dept. of Electrical Engineering Mumbai India Indian Institute of Technology Tirupati India Dept. of Computer Science Engineering Tirupati India University of Tokyo Dept. of Electrical Engineering Tokyo Japan

ISBN: (纸本)9798331515768

Scan chain architecture is widely employed in modern VLSI design for test applications. However, it often leads to high power consumption during testing. The architecture experiences elevated simultaneous switching activity due to non-functional input patterns applied during test time, resulting in significant peak power in the circuits. This increased power consumption can cause IR drop issues, negatively impacting the chip's yield. This paper proposes an innovative approach to reduce both peak power and routing length by effectively reordering the scan chains. Experimental results show that the proposed approach is effective for the ISCAS'89 and ITC'99 benchmark circuits and this method achieves lower peak power and routing length compared to the state of the art. © 2024 IEEE.

关键词： low power testing peak power routing constraint scan chain reordering voltage drop

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Globally Stable Neural Imitation Policies

arXiv

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arXiv 2024年

作者： Abyaneh, Amin Guzmán, Mariana Sosa Lin, Hsiu-Chin The Department of Electrical and Computer Engineering McGill University Montreal Canada The Department of Electrical and Computer Engineering Universidad Veracruzana Veracruz Mexico The School of Computer Science The Department of Electrical and Computer Engineering McGill University Montreal Canada

Imitation learning mitigates the resource-intensive nature of learning policies from scratch by mimicking expert behavior. While existing methods can accurately replicate expert demonstrations, they often exhibit unpredictability in unexplored regions of the state space, thereby raising major safety concerns when facing perturbations. We propose SNDS, an imitation learning approach aimed at efficient training of scalable neural policies while formally ensuring global stability. SNDS leverages a neural architecture that enables the joint training of the policy and its associated Lyapunov candidate to ensure global stability throughout the learning process. We validate our approach through extensive simulations and deploy the trained policies on a real-world manipulator arm. The results confirm SNDS's ability to address instability, accuracy, and computational intensity challenges highlighted in the literature, positioning it as a promising solution for scalable and stable policy learning in complex environments. © 2024, CC BY.

关键词： Contrastive Learning

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