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Long-Distance Transmon Coupler with cz-Gate Fidelity above 99.8%

PRX Quantum 2023年第1期4卷 010314-010314页

作者： Fabian Marxer Antti Vepsäläinen Shan W. Jolin Jani Tuorila Alessandro Landra Caspar Ockeloen-Korppi Wei Liu Olli Ahonen Adrian Auer Lucien Belzane Ville Bergholm Chun Fai Chan Kok Wai Chan Tuukka Hiltunen Juho Hotari Eric Hyyppä Joni Ikonen David Janzso Miikka Koistinen Janne Kotilahti Tianyi Li Jyrgen Luus Miha Papic Matti Partanen Jukka Räbinä Jari Rosti Mykhailo Savytskyi Marko Seppälä Vasilii Sevriuk Eelis Takala Brian Tarasinski Manish J. Thapa Francesca Tosto Natalia Vorobeva Liuqi Yu Kuan Yen Tan Juha Hassel Mikko Möttönen Johannes Heinsoo IQM Quantum Computers Espoo 02150 Finland IQM Quantum Computers Munich 80636 Germany Quantum Computing and Devices (QCD) Laboratories Quantum Technology Finland (QTF) Centre of Excellence Department of Applied Physics Aalto University Aalto 00076 Finland VTT Technical Research Centre of Finland Quantum Technology Finland (QTF) Center of Excellence VTT 02044 Finland

Tunable coupling of superconducting qubits has been widely studied due to its importance for isolated gate operations in scalable quantum processor architectures. Here, we demonstrate a tunable qubit-qubit coupler based on a floating transmon device, which allows us to place qubits at least 2 mm apart from each other while maintaining over 50-MHz coupling between the coupler and the qubits. In the introduced tunable-coupler design, both the qubit-qubit and the qubit-coupler couplings are mediated by two waveguides instead of relying on direct capacitive couplings between the components, reducing the impact of the qubit-qubit distance on the couplings. This leaves space for each qubit to have an individual readout resonator and a Purcell filter, which is needed for fast high-fidelity readout. In addition, simulations show that the large qubit-qubit distance significantly lowers unwanted non-nearest-neighbor coupling and allows multiple control lines to cross over the structure with minimal crosstalk. Using the proposed flexible and scalable architecture, we demonstrate a controlled-Z gate with (99.81±0.02)% fidelity.

关键词： Quantum benchmarking Quantum gates

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A Novel Explainable CNN Model for Screening COVID-19 on X-ray Images

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Computer Systems Science & Engineering 2023年第8期46卷 1789-1809页

作者： Hicham Moujahid Bouchaib Cherradi Oussama El Gannour Wamda Nagmeldin Abdelzahir Abdelmaboud Mohammed Al-Sarem Lhoussain Bahatti Faisal Saeed Mohammed Hadwan EEIS Laboratory ENSET of MohammediaHassan II University of CasablancaMohammedia28820Morocco STIE Team CRMEF Casablanca-SettatThe Provincial Section of El JadidaEl Jadida24000Morocco Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Information Systems King Khalid UniversityMuhayel Aseer61913Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Department of Computer Science University of Sheba RegionMarib14400Yemen DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Information Technology College of ComputerQassim UniversityBuraydah 51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaiz6803Yemen

Due to the rapid propagation characteristic of the Coronavirus(COVID-19)disease,manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of ***,new automated diagnostic methods have been brought on board,particularly methods based on artificial intelligence using different medical data such as X-ray *** imaging,for example,produces several image types that can be processed and analyzed by machine and deep learning methods.X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging *** this paper,we propose a novel Convolutional Neural Network(CNN)model(COV2Net)that can detect COVID-19 virus by analyzing the X-ray images of suspected *** model is trained on a dataset containing thousands of X-ray images collected from different *** model was tested and evaluated on an independent *** order to approve the performance of the proposed model,three CNN models namely Mobile-Net,Residential Energy Services Network(Res-Net),and Visual Geometry Group 16(VGG-16)have been implemented using transfer learning *** experiment consists of a multi-label classification task based on X-ray images for normal patients,patients infected by COVID-19 virus and other patients infected with *** proposed model is empowered with Gradient-weighted Class Activation Mapping(Grad-CAM)and Grad-Cam++techniques for a visual explanation and methodology debugging *** finding results show that the proposed model COV2Net outperforms the state-of-the-art methods.

关键词： Artificial intelligence intelligent diagnostic systems decisionmaking COVID-19 convolutional neural network

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An Overview of Tools and Techniques in Network Forensics

An Overview of Tools and Techniques in Network Forensics

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Information technology (ACIT)

作者： Mahmoud Asassfeh Mohammad Rasmi Al-Mousa Hasan Al-Dweikat Malak Hamad Al-Mashagbeh Suha Afaneh Ghassan Samara Ali Abu Zaid Mohammed Khouj Essam Al Daoud Department of Cybersecurity Zarqa University Zarqa Jordan Cybersecurity and Cloud Computing Department Applied Science Private University Amman Jordan Department of Computer Science Zarqa University Zarqa Jordan Department of Electrical Engineering University of Business and Technology Jeddah Saudi Arabia Faculty of Information Technology Zarqa University Zarqa Jordan

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

Network forensics pertains to a subfield of digital forensics that deals with network security. It is utilized in conjunction with computer network traffic monitoring and analysis, which acts as an intrusion detection system and firewall and facilitates the collection of data and digital proof for network security. This platform is designed to analyze and monitor data in a real-time network environment. It is a crucial instrument for identifying and resolving instances of real-time network misuse. This research shows the differences between network forensics and digital forensics as well as the tools and techniques used in network forensics. It also discusses building forensics platforms, developing network analysis methodologies, and talking about the future of network forensics.

关键词： Performance evaluation Digital forensics Intrusion detection Network analyzers Network security Search problems Real-time systems Logic Monitoring Stress

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Recent Advancements in Manipulator-Equipped Unmanned Aerial Vehicles (UAVs)

Recent Advancements in Manipulator-Equipped Unmanned Aerial ...

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Innovative Engineering Sciences and Technological Research (ICIESTR), International Conference on

作者： Faizan Zahid Ghulam E Mustafa Abro Zainab Alansari Department of Electrical Electronics and Computer Engineering University of Catania Italy Interdisciplinary Research Centre for Aviation and Space Exploration King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia College of Computing and Information Sciences University of Technology and Applied Sciences Muscat Oman

ISBN: (数字)9798350348637

ISBN: (纸本)9798350348644

This brief review paper aims to discuss and show a technical analysis of latest progress in manipulator equipped Unmanned Aerial Vehicles (UAVs). A manipulator can increase the robustness and adaptability of UAV, but it can also have an impact on how well it performs. The installation of a manipulator can lead to several issues, such as the UAV being unstable because of the added weight, sluggish convergence, and path planning mistakes. Therefore, this review paper shows a few latest techniques and methodologies that are adopted in order to overcome the above issues. This brief paper discusses the challenges with UAVs equipped with robotic or cable-driven manipulators along with previously contributed research work and their limitations. An extensive assessment of the limitations and their technical analysis make this brief review one of its kinds.

关键词： Reviews Manipulators Autonomous aerial vehicles Robustness Path planning Convergence

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A consistent and conservative diffuse-domain lattice Boltzmann method for multiphase flows in complex geometries

arXiv

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arXiv 2023年

作者： Liu, Xi Zhan, Chengjie Chen, Ying Chai, Zhenhua Shi, Baochang School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan430074 China Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 China

Modeling and simulation of multiphase flows in complex geomerties are challenging due to the complexity in describing the interface topology changes among different phases and the difficulty in implementing the boundary conditions on the irregular solid surface. In this work, we first developed a diffuse-domain (DD) based phase-field model for multiphase flows in complex geometries. In this model, the irregular fluid region is embedded into a larger and regular domain by introducing a smooth characteristic function. Then, the reduction-consistent and conservative phase-field equation for the multiphase field and the consistent and conservative Navier-Stokes equations for the flow field are reformulated as the diffuse-domain based consistent and conservative (DD-CC) equations where some additional source terms are added to reflect the effects of boundary conditions. In this case, there is no need to directly treat the complex boundary conditions on the irregular solid surface, and additionally, based on a matched asymptotic analysis, it is also shown that the DD-CC equations can converge to the original governing equations as the interface width parameter tends to zero. Furthermore, to solve the DD-CC equations, we proposed a novel and simple lattice Boltzmann (LB) method with a Hermite-moment-based collision matrix which can not only keep consistent and conservation properties, but also improve the numerical stability with a flexible parameter. With the help of the direct Taylor expansion, the macroscopic DD-CC equations can be recovered correctly from the present LB method. Finally, to test the capacity of LB method, several benchmarks and complex problems are considered, and the numerical results show that the present LB method is accurate and efficient for the multiphase flows in complex geomerties. © 2023, CC BY.

关键词： Boundary conditions

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A General Fourth-Order Mesoscopic Multiple-Relaxation-Time Lattice Boltzmann Model and Equivalent Macroscopic Finite-Difference Scheme for Two-Dimensional Diffusion Equations

SSRN

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SSRN 2023年

作者： Chen, Ying Chai, Zhenhua Shi, Baochang School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan430074 China Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 China

In this work, we first develop a general mesoscopic multiple-relaxation-time lattice Boltzmann (MRT-LB) model for the two-dimensional diffusion equation with the constant diffusion coefficient and source term, where the D2Q5 (five discrete velocities in two-dimensional space) lattice structure is considered. Then we exactly derive the equivalent macroscopic finite-difference scheme of the MRT-LB model. Additionally, we also propose a proper MRT-LB model for the diffusion equation with a linear source term, and obtain an equivalent macroscopic six-level finite-difference scheme. After that, we conduct the accuracy and stability analysis of the finite-difference scheme and the mesoscopic MRT-LB model. It is found that at the diffusive scaling, both of them can achieve a fourth-order accuracy in space based on the Taylor expansion. The stability analysis also shows that they are both unconditionally stable. Finally, some numerical experiments are conducted, and the numerical results are also consistent with our theoretical analysis. © 2023, The Authors. All rights reserved.

关键词： Finite difference method

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Estimating the transfer factor of natural radionuclides from soil to food chain pathways at a farmland in the southwestern Nigeria

Research Square

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Research Square 2024年

作者： Oladapo, O.O. Lawal, M.K. Ajiboye, O. Aremu, A.A. Oni, E.A. Ayanlola, P.S. Department of Science Laboratory Technology Ladoke Akintola University Oyo State Ogbomoso Nigeria Department of Mathematical and Computing Sciences KolaDaisi University Oyo State Ibadan Nigeria Department of Pure and Applied Physics Ladoke Akintola University Oyo State Ogbomoso Nigeria

The transfer factors of naturally existing radionuclides (NRs) from soil to food chain pathways on a farmland in southwestern Nigeria were estimated by measuring the activity concentrations of NRs in 20 soil samples taken from the study site using sodium iodide NaI(Ti) spectrometer detector. According to the results, the mean activity concentrations of 238U, 232Th, and 40K were 12.53±4.66 Bq/kg, 20.76±7.51 Bq/kg, and 310.79±85.91Bq/kg, respectively. These results fell below the recommended upper limit of NRs in soil. The calculated outdoor absorbed dose rate (DR), radium equivalent activity (Re) and gamma representative index (Iγ) were 32.02nGyh-1, 66.15 Bq/kg and 0.5 Bq/kg respectively. The DR, Re and Iγ were within the recommended range. The activity concentrations of 238U and 232Th in the vegetation and in the meat and milk produced by grazing animals on the farm were estimated. 238U and 232Th were estimated to be present in vegetation at concentrations of 0.2572 and 1.9049 (Bq/kg), respectively;in cow milk produced from cow grazing at the research site, the concentrations were 2.408 and 1.714 (Bq/L) and;in cow meat, they were 0.802 and 0.175 (Bq/kg). These values are considerably safe and may not pose significant health concerns when food processed at the study site is consumed. The calculated transfer factors from soil into vegetation for 238U and 232Th were 0.02 and 0.0903 respectively while those from soil into cow milk were 1.902e-4 and 8.256e-6, respectively;those from soil into cow meat were 6.4e-5 and 8.43e-7 respectively. © 2024, CC BY.

关键词： Radiation hazards

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Multiclass skin lesion classification using deep learning networks optimal information fusion

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Discover applied Sciences 2024年第6期6卷 1-13页

作者： Khan, Muhammad Attique Hamza, Ameer Shabaz, Mohammad Kadry, Seifeine Rubab, Saddaf Bilal, Muhammad Abdullah Akbar, Muhammad Naeem Kesavan, Suresh Manic Department of Computer Science HITEC University Taxila Pakistan Model Institute of Engineering and Technology Jammu India Department of Applied Data Science Noroff University College Oslo Norway Department of Computer Engineering College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Department of CS SEECS NUST Islamabad Pakistan National University of Sciences and Technology (NUST) Islamabad Pakistan Department of Electrical and Communication Engineering National University of Science and Technology Muscat Sultanate of Oman

A serious, all-encompassing, and deadly cancer that affects every part of the body is skin cancer. The most prevalent causes of skin lesions are UV radiation, which can damage human skin, and moles. If skin cancer is discovered early, it may be adequately treated. In order to diagnose skin lesions with less effort, dermatologists are increasingly turning to machine learning (ML) techniques and computer-aided diagnostic (CAD) systems. This paper proposes a computerized method for multiclass lesion classification using a fusion of optimal deep-learning model features. The dataset used in this work, ISIC2018, is imbalanced; therefore, augmentation is performed based on a few mathematical operations. After that, two pre-trained deep learning models (DarkNet-19 and MobileNet-V2) have been fine-tuned and trained on the selected dataset. After training, features are extracted from the average pool layer and optimized using a hybrid firefly optimization technique. The selected features are fused in two ways: (i) original serial approach and (ii) proposed threshold approach. Machine learning classifiers are used to classify the chosen features at the end. Using the ISIC2018 dataset, the experimental procedure produced an accuracy of 89.0%. Whereas, 87.34, 87.57, and 87.45 are sensitivity, precision, and F1 score respectively. At the end, comparison is also conducted with recent techniques, and it shows the proposed method shows improved accuracy along with other performance measures.

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Optimizing Phishing URL Detection: A Comparative Analysis of Feature Counts and Training Times

Optimizing Phishing URL Detection: A Comparative Analysis of...

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Intelligent computing, Communication, Networking and Services (ICCNS), International Conference on

作者： Moayyad Alajlouni Yahya Tashtoush Saud Alhajaj Al. Dossari Omar Darwish Department of Computer Science Jordan University of Science and Technology Irbid Jordan Department of Electrical Engineering Prince Sattam bin Abdulaziz University Wadi Addwasir Saudi Arabia Information Security and Applied Computing Department Eastern Michigan University Ypsilanti MI USA

ISBN: (数字)9798350354690

ISBN: (纸本)9798350354706

Phishing attacks are the biggest cybersecurity threats in the digital world. Attackers exploit users by impersonating real, authentic web sites to obtain sensitive information such as passwords and bank statements. One common technique used in these attacks is malicious URLs. These malicious URLs mimic legitimate URLs, misleading users into interacting with malicious websites. This practice, URL phishing, presents a big threat to internet security, emphasizing the need for advanced detection methods. This paper presents a method for detecting malicious URLs using statistical features extracted from n-grams. These n-grams are extracted from the hexadecimal representation of URLs. We used Explainable AI (XAI) to explore the extracted features and evaluate their importance and role in phishing detection. A key advantage of our method is its ability to reduce the required features and the training time by using fewer features after applying XAI techniques. Our technique only uses statistical features extracted from n-grams and the n-gram itself, without requiring any high-level features. We applied XAI techniques, SHapley Additive exPlanations (SHAP), and Local Interpretable Model-agnostic Explanations (LIME). Through the explanation provided by XAI methods, we were able to determine the most important features in our feature set, enabling a reduction in feature count. Using fewer features (4, 7, 10, 13, 15), we got good accuracy compared to the 41 features and 87 features used in the original experiment and reduced the models' training times and complexity. This research aimed to enhance phishing URL detection by optimizing feature selection and analyzing the impact on training times. Our findings show the importance of using minimal statistical features to identify malicious URLs effectively and efficiently.

关键词： Training Uniform resource locators Accuracy Phishing Neural networks Internet security Passwords Feature extraction Computational efficiency Complexity theory

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From Monopoly to Competition: When Do Optimal Contests Prevail?

SSRN

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SSRN 2024年

作者： Deng, Xiaotie Gafni, Yotam Lavi, Ron Lin, Tao Ling, Hongyi Peking University Center on Frontiers of Computing Studies China Technion - Israel Institute of Technology University of Bath and Technion Harvard University School of Engineering and Applied Sciences 150 Western Ave AllstonMA02134 United States ETH Zürich Switzerland

We study competition among multiple contest designers in a general model. The goal of each contest designer is to maximize the sum of efforts of the contestants participating in their contest. Assuming symmetric contestants, our main result shows that the optimal contests in the monopolistic setting (i.e., those that maximize the sum of efforts in a model with a single contest designer) form an equilibrium in the model with competition. Under a very natural assumption, these contests are dominant, and the equilibrium that they form is unique. Moreover, the equilibria with the optimal contests are Pareto-optimal even when other equilibria emerge. In many natural cases, they also maximize the social welfare. Additional examples show that, with further generalizations of our model, optimal contests no longer prevail. Our results therefore highlight and clarify the borderline between settings in which optimal contests prevail and do not prevail. © 2024, The Authors. All rights reserved.

关键词： Pareto principle

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