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Ideal type-Ⅱ Weyl points in topological circuits

National science Review 2021年第7期8卷 205-210页

作者： Rujiang Li Bo Lv Huibin Tao Jinhui Shi Yidong Chong Baile Zhang Hongsheng Chen Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation College of Information Science and Electronic Engineering Zhejiang University ZJU-Hangzhou Global Science and Technology Innovation Center Key Laboratory of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Zhejiang University Key Laboratory of In-Fiber Integrated Optics of Ministry of Education College of Physics and Optoelectronic Engineering Harbin Engineering University School of Software Engineering Xi'an Jiaotong University Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Centre for Disruptive Photonic Technologies Nanyang Technological University

Weyl points(WPs), nodal degenerate points in three-dimensional(3 D) momentum space, are said to be‘ideal' if they are symmetry-related and well-separated, and reside at the same energy and far from nontopological bands. Although type-II WPs have unique spectral characteristics compared with type-I counterparts, ideal type-II WPs have not yet been reported because of a lack of an experimental platform with enough flexibility to produce strongly tilted dispersion bands. Here, we experimentally realize a topological circuit that hosts only topological bands with a minimal number of four ideal type-II WPs. By stacking two-dimensional(2 D) layers of inductor-capacitor(LC) resonator dimers with the broken parity inversion symmetry(P), we achieve a strongly tilted band structure with two group velocities in the same direction, and topological surface states in an incomplete bandgap. Our results establish an ideal system for the further study of Weyl physics and other exotic topological phenomena.

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Image-to-Image Translation Based Face Photo De-Meshing Using Gans

SSRN

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SSRN 2023年

作者： Jabbar, Abdul Assam, Muhammad Shloul, Tamara Al Hameed, Hala Abdel Al-Kahtani, Noor Alkahtani, Hend Khalid Ghamry, Nivin A. Tag El Din Bro, Wahii Elsayed M. Amin, Muhammad Shoib College of Computer Science and Technology Zhejiang University Hangzhou310027 China School of Software Engineering East China Normal University Shanghai200050 China Liwa College of Technology College of Business administration United Arab Emirates Khaybar Applied College Taibah University Saudi Arabia Department of Health Information Management and Technology College of Public Health Imam Abdulrahman Bin Faisal University Saudi Arabia Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh11671 Saudi Arabia Faculty of Computers and Artificial intelligence Cairo University Giza Egypt Faculty of Engineering and Technology Future University New Cairo11835 Egypt

Most of the existing face photo de-meshing methods have accomplished promising results;there are certain quality problems with these methods like the inpainted regions would appear blurry and unpleasant boundaries becoming visible. Such artifacts cause generated face photos unreal. Therefore, we propose an effective image-to-image translation framework called Face De-meshing Using Generative Adversarial Networks (De-mesh GANs). The De-mesh GANs is a two-stage model: (i) binary mask generating module, is a three convolution layers-based encoder-decoder network architecture that automatically generates a binary mask for the meshed region, and (ii) face photo de-meshing module, is a GANs-based network that eliminates the mesh mask and synthesizes the meshed area. An arrangement of careful losses (reconstruction loss, adversarial loss, and perceptual loss) is used to reassure the better quality of the de-mesh face photos. To facilitate the training of the proposed model, we have designed a dataset of clean/corrupted photo pairs using the CelebA dataset. Qualitative and quantitative evaluations of the De-mesh GANs on real-world corrupted face photo images show better performance than the previously proposed face photo de-meshing models. Furthermore, we also offer the ablation study for performance assessment of the additional network i.e., perceptual network. © 2023, The Authors. All rights reserved.

关键词： Generative adversarial networks

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A Survey on Explainable Artificial Intelligence for Cybersecurity

arXiv

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arXiv 2023年

作者： Rjoub, Gaith Bentahar, Jamal Wahab, Omar Abdel Mizouni, Rabeb Song, Alyssa Cohen, Robin Otrok, Hadi Mourad, Azzam King Hussein School of Computing Sciences Princess Sumaya University for Technology Jordan Concordia Institute for Information Systems Engineering Concordia University Montreal Canada Department of Computer and Software Engineering Polytechnique Montréal Montréal Canada Electrical Engineering and Computer Science Department Khalifa University Abu Dhabi United Arab Emirates Department of EECS Khalifa University Abu Dhabi United Arab Emirates David R. Cheriton School of Computer Science University of Waterloo Canada Cyber Security Systems and Applied AI Research Center Dept. of CSM Lebanese American University Lebanon Division of Science New York University Abu Dhabi United Arab Emirates

The "black-box" nature of artificial intelligence (AI) models has been the source of many concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a rapidly growing research field that aims to create machine learning models that can provide clear and interpretable explanations for their decisions and actions. In the field of cybersecurity, XAI has the potential to revolutionize the way we approach network and system security by enabling us to better understand the behavior of cyber threats and to design more effective defenses. In this survey, we review the state of the art in XAI for cybersecurity and explore the various approaches that have been proposed to address this important problem. The review follows a systematic classification of cybersecurity threats and issues in networks and digital systems. We discuss the challenges and limitations of current XAI methods in the context of cybersecurity and outline promising directions for future research. © 2023, CC BY.

关键词： Cybersecurity

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SCMC: Smart city measurement and control process for data security with data mining algorithms

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Measurement: Sensors 2024年 31卷

作者： Selvarajan, Shitharth Manoharan, Hariprasath Goel, Sonali Akili, Chiranjeevi Prakash Murugesan, S. Joshi, Vaishali School of Built Environment Engineering and Computing Leeds Beckett University Leeds LS1 3HE United Kingdom Department of Electronics and Communication Engineering Panimalar Engineering College Poonamallee Tamil Nadu Chennai 600123 India Department of Electrical Engineering ITERSOA Deemed to be University Odisha Bhubaneswar India Software Engineer US Technology International Pvt Ltd India Department of Computer Science and Engineering R.M.D Engineering College Kavaraipettai 601206 India School of CSIT Symbiosis University of Applied Sciences Indore India

In this paper the importance of monitoring smart city with integration of sensors and Internet of Things (IoT) is discussed with establishment of node control process. To describe the feature of smart cities time measurements are considered with one hop distance between various nodes. Hence the system model is established for various parameters that are integrated with K-means algorithm for clustering and C4.5 for classification. As a result of combining the dual algorithms with system model it is possible to establish a secured state for each data with proper response factor. The major significance of proposed method is to introduce node point where all increasing queues in smart cities are controlled due to the information that is achieved from every data points. Moreover the improvement in projected model can be observed with four scenarios where security at every data point plays an important role at an increased level of 84%. In addition to security the amount of stable points is increased with reduction in disparities for about 2% thereby every applications in smart cities are monitored in a precise way. © 2023 The Authors

关键词： Measurement and control Security Sensors Smart city

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A biometric and physically unclonable function–Based authentication protocol for payload exchanges in internet of drones

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e-Prime - Advances in Electrical Engineering, Electronics and Energy 2024年 7卷

作者： Nyangaresi, Vincent Omollo Al-Joboury, Istabraq M. Al-sharhanee, Kareem Ali Najim, Ali Hamzah Abbas, Ali Hashim Hariz, Hussein Muhi Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and Technology Bondo 40601 Kenya Department of Applied Electronics Saveetha School of Engineering SIMATS Tamilnadu Chennai India Department of Medical Instruments Technical Engineering Al-Bayan University Technical College of Engineering Iraq Department of Communication Technical Engineering College of Engineering Techniques Al-Farahidi University Iraq Department of Computer Technical Engineering Imam Al-Kadhum College (IKC) Iraq College of Information Technology Imam Ja'afar Al-Sadiq University Al-Muthanna 66002 Iraq Department of Computer Techniques Engineering Mazaya University College Dhi-Qar Annasiriyah 64001 Iraq

Internet of Drones (IoD) has been deployed in numerous military and civilian domains to offer services such as target surveillance, traffic monitoring, disaster handling and environmental monitoring. However, message exchanges among the drones and ground station servers are via insecure wireless channels. In addition, drones may be deployed in hostile and unattended locations. This renders the IoD susceptible to numerous privacy and security threats such as drone capture and cloning. Therefore, many security solutions have been developed based on techniques such as blockchain and public key infrastructure. However, majority of these schemes are still susceptible to many attacks while some of them are inefficient for the resource-limited IoD devices. In this paper, a Physically Unclonable Function (PUF) challenge-response and biometric based robust authentication protocol is presented. Its formal security is carried out using the Real or Random (RoR) model, which demonstrates the robustness of the negotiated session key. In addition, its semantic analysis shows that it can withstand typical IoD attacks such as impersonation, replay, de-synchronization and spoofing. In terms of performance, it is shown to incur lower computation, energy and communication costs. © 2024 The Author(s)

关键词： Attacks Authentication Drones Privacy Security UAVs

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A Feature Subset Selection Method Based on the Combination of PCA and Improved GA

A Feature Subset Selection Method Based on the Combination o...

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International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI)

作者： Yinghao Li Kai Shi Fuqiang Qiao Hongyu Luo School of Computer Science and Engineering Tianjin University of Technology China College of Software and Communication Tianjin Sino-German University of Applied Sciences China

ISBN: (数字)9781728196381

ISBN: (纸本)9781728196398

Nowadays, intrusion detection data has redundant features, which leads to unsatisfactory detection results. This paper proposes a feature selection method based on the combination of principal component analysis (PCA) and improved Genetic algorithm(GA). First, PCA is used to reduce the dimensionality of the intrusion data, and the cosine similarity is used to calculate angles between the principal component and the original feature; the feature with high cosine similarity to the principal component is selected and the genetic algorithm is input, and the improved inter-group crossover strategy is adopted to reduce the probability of entering the local optimum. The fitness function of the genetic algorithm is the detection rate, and the optimal feature subset is selected as the intrusion detection data feature. Experimental results show that this method can improve the efficiency of intrusion detection and improve the classification ability of the classifier.

关键词： Machine learning algorithms Diversity reception Intrusion detection Probability Feature extraction Principal component analysis Genetic algorithms

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Text Mining A Decade Of Focal Development Trends In An African Country

Text Mining A Decade Of Focal Development Trends In An Afric...

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International Conference on Wavelet Active Media technology and Information Processing (ICWAMTIP)

作者： Opoku-Mensah Nelson Qin Zhiguang Gyamfi Enoch Opanin Danso Juliana Mantebea Nyame Gabriel School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu St. Monica's College of Education Mampong Ghana C.K. Tedam University of Technology and Applied Sciences Navrongo Ghana Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development Kumasi Ghana

ISBN: (纸本)9781665413657

This paper identified the emerging developmental trends of Ghana, an African country, based on online and offline textual, video and audio data sources from 2008 to 2018. In all, about 9,501 text files were collected and where needed, transcribed from these sources and content analyzed by series of text mining processes to bring out the convention for all the combined years. Topic modeling was the main adopted text mining technique. We initiated the topic modeling with the term frequency approach. The results from the mining processes were conceptually presented in relative frequency table and visually summarized as word clouds to map meaningful findings that were logically and humanly understandable. Through this approach, 45 major developmental themes emerged of which education seems to be the most frequently discussed trend in Ghanaian politics and government. In conclusion governments can detect developmental layouts from textual data.

关键词： Text mining Soft sensors Government Education Layout Africa Media

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Quantum Linear System Solvers: A Survey of Algorithms and Applications

arXiv

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arXiv 2024年

作者： Morales, Mauro E.S. Pira, Lirandë Schleich, Philipp Koor, Kelvin Costa, Pedro C.S. An, Dong Aspuru-Guzik, Alán Lin, Lin Rebentrost, Patrick Berry, Dominic W. Joint Center for Quantum Information and Computer Science University of Maryland United States Centre for Quantum Software and Information University of Technology Sydney Australia Centre for Quantum Technologies National University of Singapore Singapore Department of Computer Science University of Toronto Canada Vector Institute for Artificial Intelligence Toronto Canada ContinoQuantum Sydney Australia Beijing International Center for Mathematical Research Peking University Beijing China Department of Chemistry University of Toronto Canada Canadian Institute for Advanced Research Toronto Canada Acceleration Consortium Toronto Canada Department of Chemical Engineering & Applied Chemistry University of Toronto Toronto Canada Department of Materials Science & Engineering University of Toronto Toronto Canada Lebovic Fellow Canadian Institute for Advanced Research Toronto Canada Department of Mathematics University of California Berkeley United States Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory Berkeley United States Department of Computer Science National University of Singapore Singapore School of Mathematical and Physical Sciences Macquarie University Sydney Australia

Solving linear systems of equations plays a fundamental role in numerous computational problems from different fields of science. The widespread use of numerical methods to solve these systems motivates investigating the feasibility of solving linear systems problems using quantum computers. In this work, we provide a survey of the main advances in quantum linear systems algorithms, together with some applications. We summarize and analyze the main ideas behind some of the algorithms for the quantum linear systems problem in the literature. The analysis begins by examining the Harrow-Hassidim-Lloyd (HHL) solver. We note its limitations and reliance on computationally expensive quantum methods, then highlight subsequent research efforts which aimed to address these limitations and optimize runtime efficiency and precision via various paradigms. We focus in particular on the post-HHL enhancements which have paved the way towards optimal lower bounds with respect to error tolerance and condition number. By doing so, we propose a taxonomy that categorizes these studies. Furthermore, by contextualizing these developments within the broader landscape of quantum computing, we explore the foundational work that have inspired and informed their development, as well as subsequent refinements. Finally, we discuss the potential applications of these algorithms in differential equations, quantum machine learning, and many-body physics. © 2024, CC BY.

关键词： Quantum computers

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Utilising physics-guided deep learning to overcome data scarcity

arXiv

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arXiv 2022年

作者： Bai, Jinshuai Alzubaidi, Laith Wang, Qingxia Kuhl, Ellen Bennamoun, Mohammed Gu, Yuantong School of Mechanical Medical and Process Engineering Queensland University of Technology BrisbaneQLD4000 Australia ARC Industrial Transformation Training Centre -Joint Biomechanics Queensland University of Technology BrisbaneQLD4000 Australia Centre for Applied Climate Sciences University of Southern Queensland ToowoombaQLD4305 Australia School of Civil Engineering The University of Queensland BrisbaneQLD4072 Australia Department of Mechanical Engineering Stanford University StanfordCA United States Department of Computer Science and Software Engineering The University of Western Australia PerthWA Australia

Deep learning (DL) relies heavily on data, and the quality of data influences its performance significantly. However, obtaining high-quality, well-annotated datasets can be challenging or even impossible in many real-world applications, such as structural risk estimation and medical diagnosis. This presents a significant barrier to the practical implementation of DL in these fields. Physics-guided deep learning (PGDL) is a novel type of DL that can integrate physics laws to train neural networks. This can be applied to any systems that are controlled or governed by physics laws, such as mechanics, finance and medical applications. It has been demonstrated that, with the additional information provided by physics laws, PGDL achieves great accuracy and generalisation in the presence of data scarcity. This review provides a detailed examination of PGDL and offers a structured overview of its use in addressing data scarcity across various fields, including physics, engineering and medical applications. Moreover, the review identifies the current limitations and opportunities for PGDL in relation to data scarcity and offers a thorough discussion on the future prospects of PGDL. Copyright © 2022, The Authors. All rights reserved.

关键词： Medical applications

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Strong Shadow Removal of Text Document Images Based on Background Estimation and Shading Scale

Strong Shadow Removal of Text Document Images Based on Backg...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Bingshu Wang Shuang Feng C.L. Philip Chen School of Software Northwestern Polytechnical University Taicang Campus Suzhou China School of Applied Mathematics Research Center for Applied Mathematics and Interdisciplinary Science Beijing Normal University Zhuhai China School of Computer Science and Engineering South China University of Technology Guangzhou China Faculty of Science and Technology University of Macau Macau China

ISBN: (数字)9781728162461

ISBN: (纸本)9781665419352

Shadows may bring uncomfortable perception when taking text document images. Previous work mainly focuses on weak shadow removal issue. However, strong shadow removal is still a challenging task. This paper proposes a method based on background estimation and shading scale to remove strong shadows from text document images. Firstly, background color estimation is designed by a number of iterations through neighboring pixels' propagation. Then, umbra and penumbra are separated by morphological operations and processed by a divide-and-conquer strategy. For umbra, shading scale strategy is exploited to obtain unshadowed result. For penumbra, background replace strategy is designed to remove the shadow regions. Finally, a reference background and a text binary image are combined to generate unshadowed image. Experiments conducted on some typical strong shadow images demonstrate the effectiveness of our method.

关键词： Image color analysis Estimation Task analysis Cybernetics Morphological operations

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