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Cryptanalysis of DBST, a lightweight block cipher

Frontiers of computer science 2024年第4期18卷 219-221页

作者： Sadegh SADEGHI Nasour BAGHERI Department of Mathematics Institute for Advanced Studies in Basic Sciences(IASBS)Zanjan 45137-66731Iran Research Center for Basic Sciences and Modern Technologies(RBST) Institute for Advanced Studies in Basic Sciences(IASBS)Zanjan 45137-66731Iran Electrical Engineering Department Shahid Rajaee Teacher Training UniversityTehran 16788-15811Iran School of Computer Science(SCS) Institute for Research in Fundamental Sciences(IPM)Tehran 19395-5531Iran

1 Introduction Conventional cryptographic primitives are not suitable for resource-constrained ***,numerous lightweight primitives have been proposed over the past decade,specifically tailored for such ***,such ciphers would not be used in a real-world application unless they were thoroughly tested for security against existing *** this direction,DBST[1]cipher has been recently proposed by Yan et *** balance security,cost,and efficiency,DBST has implemented a novel 4-branch generalized Feistel variant *** this structure,a 2-branch XOR operation has been incorporated in the middle section,establishing interconnections between all *** the other hand,by leveraging the bit-slice technique and subkeys,the algorithm introduces an innovative approach to constructing a dynamic S-box *** designers of DBST cipher have extensively investigated its resistance to known attacks such as linear and differential cryptanalysis,as well as impossible differential cryptanalysis,among *** them,the objective of differential cryptanalysis[2]is to identify high-probability characteristics in the plaintext that are transmitted to the ciphertext,known as distinguishers.

关键词： structure. primitive branch

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Corrugated Silicon Nitride Masks with Enhanced Mechanical Strength for Patterning RGB-Stripe OLED Microdisplays

Corrugated Silicon Nitride Masks with Enhanced Mechanical St...

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International Symposium, Seminar, and Exhibition, Display Week 2024

作者： Dong, Shou-Cheng Yang, Jiye Ting Tam, Bryan Siu Tang, Ching W. State Key Laboratory of Advanced Displays and Optoelectronics Technologies Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Institute for Advanced Study The Hong Kong University of Science and Technology Hong Kong Co. Ltd Suzhou China Department of Chemical Engineering University of Rochester RochesterNY United States

Corrugated silicon nitride masks (SiNMs) with improved mechanical strength are developed for patterning OLED microdisplays. The corrugations in the nitride membrane significantly increase the rigidity of the mask and reduce sagging, enabling 3000-ppi slot apertures for patterning RGB-stripe pixel layouts that are normally not achievable by fine metal masks. © 2024, John Wiley and Sons Inc. All rights reserved.

关键词： Silicon nitride

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A Comprehensive Technique Based on Machine Learning for Device and Circuit Modeling of Gate-All-Around Nanosheet Transistors

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 181-194页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering the Institute of Biomedical Engineering the Department of Electronics and Electrical Engineering the Institute of Pioneer Semiconductor Innovation and the Institute of Artificial Intelligence Innovation Hsinchu300093 Taiwan

Machine learning (ML) is poised to play an important part in advancing the predicting capability in semiconductor device compact modeling domain. One major advantage of ML-based compact modeling is its ability to capture complex relationships and patterns in large datasets. Therefore, in this paper a novel design scheme based on dynamically adaptive neural network (DANN) is proposed to develop fast and accurate compact model (CM). This framework constitutes a powerful yet computationally efficient methodology and exhibits emergent dynamic behaviors. This paper demonstrates that the compact model based on ML can be designed to replicate the performance of conventional compact model for nanodevices. For this work, gate-all-around (GAA) nanosheet (NS) device characteristics are comprehensively analyzed for process variability sources using the proposed model. The device geometry parameters such as channel length, nanosheet width and nanosheet thickness are fed as input features to the DANN model. The adaptive neural network learns dynamically by updating weights of the model in accordance with the input features and achieves accurate neural weight convergence. The proposed model predicted the electrical characteristics of NS devices with less than 1% error rate. The model is also implemented and validated for the simulations of digital circuit designs such as inverter, and logic gates. ©;2023 The Authors.

关键词： Circuit simulation

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Subwavelength Fano Resonant Porous Silicon Metasurfaces for Sensing and Dynamic Structural Color

Subwavelength Fano Resonant Porous Silicon Metasurfaces for ...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Gafsi, Saddam Dos Santos, Estevao Marques Kravchenko, Ivan Ryckman, Judson D. Holcombe Department of Electrical and Computer Engineering Clemson University ClemsonSC29634 United States Center for Nanophase Materials Science Oak Ridge National Laboratory Oak RidgeTN37831 United States

ISBN: (纸本)9781957171395

We introduce the design, fabrication, and experimental investigation of subwavelength Fano resonant porous silicon metasurfaces functioning on the principle of guided mode resonance. These metasurfaces exhibit promise for dynamic structural coloration and sensing applications. CLEO 2024 © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Mesoporous materials

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Subwavelength Fano Resonant Porous Silicon Metasurfaces for Sensing and Dynamic Structural Color

Subwavelength Fano Resonant Porous Silicon Metasurfaces for ...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

关键词： Porous materials

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Degradation mechanism analysis of LiNi_(0.5)Co_(0.2)Mn_(0.3)O_(2) single crystal cathode materials through machine learning

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npj Computational Materials 2022年第1期8卷 2119-2127页

作者： Wuxin Sha Yaqing Guo Danpeng Cheng Qigao Han Ping Lou Minyuan Guan Shun Tang Xinfang Zhang Songfeng Lu Shijie Cheng Yuan-Cheng Cao School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan430074China State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan430074China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan430074China State Grid Huzhou Electric Power Supply Company Huzhou313000China School of Cyber Science&Engineering Huazhong University of Science and TechnologyWuhan430074China

LiNi_(0.5)Co_(0.2)Mn_(0.3)O_(2)(NCM523)has become one of the most popular cathode materials for current lithium-ion batteries due to its high-energy density and cost ***,the rapid capacity fading of NCM severely hinders its development and ***,the single crystal NCM523 materials under different degradation states are characterized using scanning transmission electron microscopy(STEM).Then we developed a neural network model with a two-sequential attention block to recognize the crystal structure and locate defects in STEM *** number of point defects in NCM523 is observed to experience a trend of increasing first and then decreasing in the degradation *** space between the transition metal columns shrinks obviously,inducing dramatic capacity *** analysis sheds light on the defect evolution and chemical transformation correlated with layered material *** also provides interesting hints for researchers to regenerate the electrochemical capacity and design better battery materials with longer life.

关键词： battery crystal analysis

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Deep CNN Model for Multimodal Medical Image Denoising

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computers, Materials & Continua 2022年第11期73卷 3795-3814页

作者： Walid El-Shafai Amira A.Mahmoud Anas M.Ali El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

In the literature,numerous techniques have been employed to decrease noise in medical image modalities,including X-Ray(XR),Ultrasonic(Us),Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and Positron Emission Tomography(PET).These techniques are organized into two main classes:the Multiple Image(MI)and the Single Image(SI)*** the MI techniques,images usually obtained for the same area scanned from different points of view are used.A single image is used in the entire procedure in the SI *** denoising techniques can be carried out both in a transform or spatial *** paper is concerned with single-image noise reduction techniques because we deal with single medical *** most well-known spatial domain noise reduction techniques,including Gaussian filter,Kuan filter,Frost filter,Lee filter,Gabor filter,Median filter,Homomorphic filter,Speckle reducing anisotropic diffusion(SRAD),Nonlocal-Means(NL-Means),and Total Variation(TV),are ***,the transform domain noise reduction techniques,including wavelet-based and Curvelet-based techniques,and some hybridization techniques are ***,a deep(Convolutional Neural Network)CNN-based denoising model is proposed to eliminate Gaussian and Speckle noises in different medical image *** model utilizes the Batch Normalization(BN)and the ReLU as a basic *** a result,it attained a considerable improvement over the traditional *** previously mentioned techniques are evaluated and compared by calculating qualitative visual inspection and quantitative parameters like Peak Signal-to-Noise Ratio(PSNR),Correlation Coefficient(Cr),and system complexity to determine the optimum denoising algorithm to be applied *** on the quality metrics,it is demonstrated that the proposed deep CNN-based denoising model is efficient and has superior denoising performance over the traditionaldenoising techniques.

关键词： Image enhancement medical imaging speckle noise Gaussian noise denoising filters CNN denoising

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A Multi-Sequence Prophet Inequality Under Observation Constraints

A Multi-Sequence Prophet Inequality Under Observation Constr...

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IEEE International Symposium on Information Theory

作者： Aristomenis Tsopelakos Olgica Milenkovic Department of Electrical and Computer Engineering Coordinated Science Laboratory University of Illinois at Urbana-Champaign

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

In our problem, we are given access to a number of sequences of nonnegative i.i.d. random variables, whose realizations are observed sequentially. All sequences are of the same finite length. The goal is to pick one element from each sequence in order to maximize a reward equal to the expected value of the sum of the selections from all sequences. The decision on which element to pick is irrevocable, i.e., rejected observations cannot be revisited. Furthermore, the procedure terminates upon having a single selection from each sequence. Our observation constraint is that we cannot observe the current realization of all sequences at each time instant. Instead, we can observe only a smaller, yet arbitrary, subset of them. Thus, together with a stopping rule that determines whether we choose or reject the sample, the solution requires a sampling rule that determines which sequence to observe at each instant. The problem can be solved via dynamic programming, but with an exponential complexity in the length of the sequences. In order to make the solution computationally tractable, we introduce a decoupling approach and determine each stopping time using either a single-sequence dynamic programming, or a Prophet Inequality inspired threshold method, with polynomial complexity in the length of the sequences. We prove that the decoupling approach guarantees at least 0.745 of the optimal expected reward of the joint problem. In addition, we describe how to efficiently compute the optimal number of samples for each sequence, and its' dependence on the variances.

关键词： Polynomials Finite element analysis Dynamic programming Complexity theory Random variables Information theory

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Adaptive Fine-Grained Feature Mining and RoI Feature Interaction Network for Small Object Detection in Aerial Images

Adaptive Fine-Grained Feature Mining and RoI Feature Interac...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Fangmin Xie Zhan Xiong Zhuoyue Wang Kun Yang Guoqiang Xiao College of Computer and Information Science Southwest University China Institute of Advanced Computer Science Leiden University Netherlands Department of Electrical Engineering and Computer Sciences University of California Berkeley Berkeley USA

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Object detection in drone view images remains challenging due to small-scale objects distributed non-uniformly and exhibiting weak semantic features. Additionally, external factors such as lighting conditions, viewing angles, and background clutter further complicate the detection of small objects. To address these issues, we propose a small object detector called Adaptive Fine-grained Feature Mining Network (AFMNet) based on an anchor-free framework. Firstly, an Adaptive Fine-grained Feature Mining (AFFM) module is designed to generate Regions of Interest (RoI) on high-resolution feature maps and mine fine-grained information that benefits the representation of small objects. Secondly, an Inter-RoI Feature Interaction (IRFI) block is developed to efficiently integrate complementary cues— namely, deep layer semantic information and shallow layer spatial details—and enhance RoI features. Experiments on the VisDrone dataset demonstrate that our method achieves state-of-the-art performance. The source code of our AFMNet is available at https://***/xiefangmin/AFMNet.

关键词： Adaptive systems Source coding Semantics Lighting Object detection Detectors Signal processing Feature extraction Speech processing Drones

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Tuning the number of chiral edge channels in a fixed quantum anomalous Hall system

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Physical Review B 2024年第20期109卷 L201402-L201402页

作者： Peng Deng Yulei Han Peng Zhang Su Kong Chong Zhenhua Qiao Kang L. Wang Beijing Academy of Quantum Information Sciences Beijing 100193 China Department of Electrical and Computer Engineering University of California Los Angeles California 90095 USA Department of Physics Fuzhou University Fuzhou Fujian 350108 China International Center for Quantum Design of Functional Materials CAS Key Laboratory of Strongly-Coupled Quantum Matter Physics and Department of Physics University of Science and Technology of China Anhui 230026 China Hefei National Laboratory University of Science and Technology of China Hefei 230088 China

Quantum anomalous Hall (QAH) insulators exhibit chiral edge channels characterized by vanishing longitudinal conductance and quantized Hall conductance of Ce2/h, wherein the Chern number C is an integer equal to the number of the parallel chiral edge channels. These chiral edge channels conduct dissipationless transport in QAH insulators, making them pivotal for applications in low-consumption electronics and topological quantum computing. While the QAH effect with multiple chiral edge channels (i.e., C > 1) has been demonstrated in multilayers consisting of magnetic topological insulators and normal insulators, the channel number remains fixed for a given sample. Here, we unveil the tunability of the number of chiral edge channels within a single QAH insulator device. By tuning the magnetization of individual layers within the multilayer system, Chern insulating states with different Chern numbers are unveiled. The tunable Chern number was corroborated by our theoretical calculations. Furthermore, we conducted layer-dependent calculations to elucidate the contribution of the Chern number from different layers in the multilayer. Our findings demonstrate an extra degree of freedom in manipulating the chiral edge channels in QAH insulators. This tunability offers an extra dimension for the implementation of the QAH-based multichannel dissipationless transport.

关键词： Quantum anomalous Hall effect Quantum transport Topological insulators Molecular beam epitaxy

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