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35th International Conference on Power Electronics and Electrical Drives, EDPE 2021

作者： Stojanović, Željko Pelin, Denis Department of Electrical Engineering Zagreb University of Applied Sciences Zagreb Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Osijek Croatia

The paper deals with the harmonic content of the input current of the voltage mode controlled boost converter in quasiperiodicity. By decrease of the input voltage the converter exhibits quasiperiodicity caused by Hopf bifurcation and border collision bifurcation. In the area of these bifurcations mode locking, quasiperiodic steady-states and chaotic steady-states alternate. Characteristic waveforms, trajectories and harmonic contents of the input currrent in the area of Hopf bifurcation and border collision bifurcation are presented. The quasiperiodicity caused by both bifurcations has so far not been recorded in the boost converter. Additional harmonics in the input current of the converter are introduced by the quasiperiodicity. These harmonics are spread to the area of frequencies lower than the switching frequency as well as between the multiple integers of the switching frequency. Low frequency AC components in quasiperiodicity caused by border collision bifurcation are higher than low frequency AC components caused by Hopf bifurcation. These low frequency harmonics can be harmful to the source of the input voltage. ©2021 IEEE.

关键词： Boost converter Border collision bifurcation Harmonic content Hopf bifurcation Quasiperiodicity

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Jointly Learned Symbol Detection and Signal Reflection in RIS-Aided Multi-user MIMO Systems 55

Jointly Learned Symbol Detection and Signal Reflection in RI...

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55th Asilomar Conference on Signals, Systems and computers, ACSSC 2021

作者： Wang, Liuhang Shlezinger, Nir Alexandropoulos, George C. Zhang, Haiyang Wang, Baoyun Eldar, Yonina C. Nanjing University of Posts and Telecommunications School of Communication and Information Engineering Nanjing China Ben-Gurion University of the Negev School of Electrical and Computer Engineering Beer-Sheva Israel National and Kapodistrian University of Athens Department of Informatics and Telecommunications Greece Weizmann Institute of Science Faculty of Math and Computer Science Rehovot Israel

ISBN: (纸本)9781665458283

Reconfigurable Intelligent Surfaces (RISs) are regarded as a key technology for future wireless communications, enabling programmable radio propagation environments. However, the passive reflecting feature of RISs induces notable challenges on channel estimation, making coherent symbol detection a challenging task. In this paper, we consider the uplink of RIS-aided multi-user Multiple-Input Multiple-Output (MIMO) systems and propose a Machine Learning (ML) approach to jointly design the multi-antenna receiver and configure the RIS reflection coefficients, which does not require explicit full knowledge of the channel input-output relationship. Our approach devises a ML-based receiver, while the configurations of the RIS reflection patterns affecting the underlying propagation channel are treated as hyperparameters. Based on this system design formulation, we propose a Bayesian ML framework for optimizing the RIS hyperparameters, according to which the transmitted pilots are directly used to jointly tune the RIS and the multi-antenna receiver. Our simulation results demonstrate the capability of the proposed approach to provide reliable communications in non-linear channel conditions corrupted by Gaussian noise. © 2021 IEEE.

关键词： MIMO systems

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Preface and Acknowledgements

Preface and Acknowledgements

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作者： Favorskaya, Margarita N. Peng, Sheng-Lung Simic, Milan Alhadidi, Basim Pal, Souvik Institute of Informatics and Telecommunication Reshetnev Siberian State University of Science and Technology Krasnoyarsk Russia Department of Creative Technologies and Product Design National Taipei University of Business Taipei City Taiwan School of Engineering RMIT University Bundoora East Campus MelbourneVIC Australia Department of Computer Information Systems Al-Balqa’ Applied University As-Salt Jordan Department of Computer Science and Engineering Global Institute of Management and Technology Kolkata India

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High-Dimensional Quantum Conference Key Agreement

High-Dimensional Quantum Conference Key Agreement

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IEEE International Symposium on Information Theory

作者： Omar Amer Walter O. Krawec Future Lab for Applied Research and Engineering JPMorgan Chase Bank N.A New York NY USA Computer Science &amp Engineering Department University of Connecticut Storrs CT

ISBN: (数字)9781665421591

ISBN: (纸本)9781665421607

Quantum Conference Key Agreement (QCKA) protocols are designed to allow multiple parties to agree on a shared secret key, secure against computationally unbounded adversaries. In this paper, we consider a high-dimensional QCKA protocol and prove its information theoretic security against arbitrary, general, attacks in the finite-key scenario. Our proof technique may be useful for other high-dimensional multiparty quantum cryptographic protocols. Finally, we evaluate the protocol in a variety of settings, showing that high-dimensional states can greatly benefit QCKA protocols.

关键词： Quantum computing Conferences Quantum mechanics Security Information theory Cryptographic protocols

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Autonomous drone swarm navigation and multi-target tracking in 3D environments with dynamic obstacles

arXiv

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arXiv 2022年

作者： Qamar, Suleman Khan, Saddam Hussain Arshad, Muhammad Arif Qamar, Maryam Khan, Asifullah Pattern Recognition Lab Department Of Computer Information Sciences Pakistan Institute Of Engineering Applied Sciences Nilore Islamabad45650 Pakistan Pakistan Institute Of Engineering Applied Sciences Nilore Islamabad 45650 Pakistan Department Of Computer Science & IT University Of Azad Jammu And Kashmir Muzaffarabad Pakistan Center For Mathematical Sciences Pakistan Institute Of Engineering Applied Sciences Nilore Islamabad 45650 Pakistan

Autonomous modeling of artificial swarms is necessary because manual creation is a time-intensive and complicated procedure which makes it impractical. An autonomous approach employing deep reinforcement learning, is presented in this study for swarm navigation. In this approach, complex 3D environments with static and dynamic obstacles along with resistive forces (like linear drag, angular drag and gravity) are modelled for tracking multiple dynamic targets. Moreover, reward functions for robust swarm formation and target tracking are devised for learning complex swarm behaviors. Since the number of agents is not fixed and have only the partial observance of the environment, therefore, swarm formation and navigation becomes challenging task. In this regard, the proposed strategy consists of three main phases to tackle the aforementioned challenges: 1) A methodology for dynamic swarm management, 2) Avoiding obstacles, Finding the shortest path towards the targets, 3) Tracking the targets, and Island modelling. The dynamic swarm management phase translates basic sensory input to high-level commands to enhance swarm navigation and decentralized setup while maintaining the swarm's size fluctuations. While, in the island modeling, the swarm can split into individual sub-swarms according to number of targets, and conversely, these sub-swarms may join to form a single huge swarm, giving the swarm ability to track multiple targets. Customized state-of-the-art policy-based deep reinforcement learning algorithms are employed to achieve significant results. The promising results show that our proposed strategy enhances swarm navigation and has the ability to track multiple static and dynamic targets in complex dynamic environments. Copyright © 2022, The Authors. All rights reserved.

关键词： Deep learning

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Comparison of Google Analytics with Similar Web for Statistical Analysis of Website Traffic 1st

Comparison of Google Analytics with Similar Web for Statisti...

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1st International Conference on Advanced Network Technologies and Computational Intelligence, ICANTCI 2024

作者： Garg, Bindu Kasar, Manisha Kotecha, Ketan Rahmani, Mohammad Khalid Imam University College of Engineering Pune India Symbiosis Center for Applied Artificial Intelligence Symbiosis Institute of Technology Symbiosis International University Pune India Department of Computer Science College of Computing and Informatics Saudi Electronic University Riyadh Saudi Arabia

ISBN: (纸本)9783031860713

This study addresses the burgeoning demand for website data collection and analysis in business operations, emphasizing the pivotal role of web analytics in providing crucial insights into customer behaviour. Despite the prevalence of various website traffic analysing tools, there exists a notable lack of comprehensive testing on the precision and reliability of these services. The research compares four key analytics measures from Google Analytics (GA) with SimilarWeb (SW) using average monthly statistics over a one-year period for 50+ websites across different nations and business verticals. Employing various statistical tests, including paired t-tests, Shapiro-Wilk tests, and correlation analysis, the study reveals statistically significant variations in key metrics between GA and SW. Notably, SimilarWeb tends to provide lower estimates for the number of visits and unique visitors compared to Google Analytics. However, the findings underscore the potential complementarity of using both tools in cases where direct access to a site’s analytics is not feasible, particularly for competitive intelligence and benchmarking purposes. The study’s extensive statistical analysis covers unique visitors, total visits, bounce rates, and average session duration, offering valuable insights into the nuanced variations and potential sources of error. There are statistically significant differences between the two web traffic tools in terms of unique visitors, total visits, average session time & bounce rates. In comparison to Google Analytics, SimilarWeb figures were on average, 40% less for unique visitors, 50% greater for average session time, 25% greater for bounce rate, and 20% lesser for total visits. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Error statistics

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Epitaxial high-K barrier AlBN/GaN HEMTs

arXiv

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arXiv 2025年

作者： Savant, Chandrashekhar Nguyen, Thai-Son Nomoto, Kazuki Vishwakarma, Saurabh Ma, Siyuan Dhar, Akshey Chen, Yu-Hsin Casamento, Joseph Smith, David J. Xing, Huili Grace Jena, Debdeep Department of Materials Science and Engineering Cornell University IthacaNY14853 United States School of Electrical and Computer Engineering Cornell University IthacaNY14853 United States School for Engineering of Matter Transport and Energy Arizona State University TempeAZ85287 United States Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Arizona State University TempeAZ85287 United States Kavli Institute at Cornell for Nanoscale Science Cornell University IthacaNY14853 United States School of Applied and Engineering Physics Cornell University IthacaNY14853 United States

We report a polarization-induced 2D electron gas (2DEG) at an epitaxial AlBN/GaN heterojunction grown on a SiC substrate. Using this 2DEG in a long conducting channel, we realize ultra-thin barrier AlBN/GaN high electron mobility transistors that exhibit current densities > 0.25 A/mm, clean current saturation, a low pinch-off voltage of -0.43 V, and a peak transconductance of ∼0.14 S/mm. Transistor performance in this preliminary realization is limited by the contact resistance. Capacitance-voltage measurements reveal that introducing ∼7 % B in the epitaxial AlBN barrier on GaN boosts the relative dielectric constant of AlBN to ΕrAlBN ∼ 16, higher than the AlN dielectric constant of ΕrAlN ∼ 9. Epitaxial high-K barrier AlBN/GaN HEMTs can thus extend performance beyond the capabilities of current GaN transistors. © 2025, CC BY-NC-ND.

关键词： Gallium nitride

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Anomaly Detection with Variance Stabilized Density Estimation

arXiv

引用

arXiv 2023年

作者： Rozner, Amit Battash, Barak Li, Henry Wolf, Lior Lindenbaum, Ofir Faculty of Engineering Bar Ilan University Ramat-Gan Israel Department of Applied Mathematics Yale University New HavenCT United States School of Computer Science Tel Aviv University Tel-Aviv Israel

We propose a modified density estimation problem that is highly effective for detecting anomalies in tabular data. Our approach assumes that the density function is relatively stable (with lower variance) around normal samples. We have verified this hypothesis empirically using a wide range of real-world data. Then, we present a variance-stabilized density estimation problem for maximizing the likelihood of the observed samples while minimizing the variance of the density around normal samples. To obtain a reliable anomaly detector, we introduce a spectral ensemble of autoregressive models for learning the variance-stabilized distribution. We have conducted an extensive benchmark with 52 datasets, demonstrating that our method leads to state-of-the-art results while alleviating the need for data-specific hyperparameter tuning. Finally, we have used an ablation study to demonstrate the importance of each of the proposed components, followed by a stability analysis evaluating the robustness of our model. © 2023, CC BY.

关键词： Anomaly detection

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Hybrid multi-criteria decision-making method with a bipolar fuzzy approach and its applications to economic condition analysis

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engineering Applications of Artificial Intelligence 2024年 132卷

作者： Jana, Chiranjibe Simic, Vladimir Pal, Madhumangal Sarkar, Biswajit Pamucar, Dragan Tamil Nadu Chennai602105 India Faculty of Transport and Traffic Engineering University of Belgrade VojvodeStepe 305 Belgrade11010 Serbia Yuan Ze University College of Engineering Department of Industrial Engineering and Management Taoyuan City320315 Taiwan Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore721102 India Department of Industrial Engineering Yonsei University 50 Yonsei-ro Sinchon-dong Seodaemun-gu Seoul03722 Korea Republic of Center for Global Health Research Saveetha Medical College Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu 600077 India Department of Industrial Engineering and Management National Taipei University of Technology Taipei City 106344 Taiwan Department of Operations Research and Statistics Faculty of Organizational Sciences University of Belgrade Belgrade Serbia Department of Computer Science and Mathematics Lebanese American University Byblos 1102 2801 Lebanon

The bipolar fuzzy set and interval-valued bipolar fuzzy set efficiently analyse real-world problems where for each input of an object, there has counter information. This study's main objective is to lay a foundation for considering a new approach to the bipolar fuzzy hybrid operators tool applied in a realistic frame that contains uncertainties. In this view, some mixed aggregation operators, namely, the hybrid bipolar fuzzy weighted averaging geometric (H-BFWAG), hybrid bipolar fuzzy order weighted averaging geometric (H-BFOWAG), hybrid interval-valued bipolar fuzzy weighted averaging geometric (H-IVBFWAG), and hybrid interval-valued bipolar fuzzy order weighted averaging geometric (H-IVBFOWAG) operators are generated in bipolar fuzzy environment. A decision making approach is developed to build the multi-criteria decision making model. A numerical example is considered to study the different effects on various Indian economic sectors in the COVID-19 environment. Managerial implications are highlighted in between many industrial sectors on which the Indian economy depends and the country's gross domestic product depends on their inter-relationship. This study investigates COVID-19's impact on society and the economy in the Indian context. A comparative investigation is introduced with some pre-existing operators and the TOPSIS (technique for order of preference by similarity to ideal solution) approach to justify the proposed method. © 2024 Elsevier Ltd

关键词： COVID-19

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Secrecy Performance Analysis of Heterogeneous Networks With Unreliable Wireless Backhaul and Imperfect Channel Estimation

Secrecy Performance Analysis of Heterogeneous Networks With ...

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作者： Yin, Cheng Garcia-Palacios, Emiliano Xiao, Pei Sharma, Vishal Dobre, Octavia A. Duong, Trung Q. University of Surrey Institute for Communication Systems Home for 5GIC and 6GIC GuildfordGU2 7XH United Kingdom Queen's University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom Memorial University Faculty of Engineering and Applied Science St. John'sNLA1B 3X5 Canada Kyung Hee University Department of Electronic Engineering yeonggi-do Yongin-si17140 Korea Republic of

Wireless backhaul is an economical and flexible alternative to wired backhaul, however, it experiences impairments. This research proposes a new secure heterogeneous system model with unreliable wireless backhaul and imperfect channel estimation over Nakagami-m fading channel. To improve the system secrecy performance, we propose three small-cell transmitter selection schemes under channel estimation imperfections and wireless backhaul impairments, namely Optimum Selection (OS), Sub-optimum Selection (SS) and Minimum-Eavesdropping Selection (MES). Novel closed-form expressions of secrecy outage probability (SOP) are derived for these three selection schemes in both practical and ideal scenarios. The novel theoretical analysis and simulation results show the impact of wireless backhaul uncertainties and channel estimation errors on system secrecy performance. In addition, we investigate how the number of small-cell transmitters affects the system secrecy performance. The asymptotic behaviour is provided to obtain insights into the system performance. The analytical derivations and asymptotic expressions are validated by Monte Carlo simulations. Our novel theoretical analysis can guide different physical layer security (PLS) designs. © 1967-2012 IEEE.

关键词： Transmitters

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