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arXiv 2024年

作者： Feng, Yujie Chu, Xu Xu, Yongxin Shi, Guangyuan Liu, Bo Wu, Xiao-Ming Department of Computing The Hong Kong Polytechnic University Hong Kong School of Computer Science Peking University Beijing China Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing China Center on Frontiers of Computing Studies Peking University Beijing China

A practical dialogue system requires the capacity for ongoing skill acquisition and adaptability to new tasks while preserving prior knowledge. However, current methods for Continual Dialogue State Tracking (DST), a crucial function of dialogue systems, struggle with the catastrophic forgetting issue and knowledge transfer between tasks. We present TaSL, a novel framework for task skill localization and consolidation that enables effective knowledge transfer without relying on memory replay. TaSL uses a novel group-wise technique to pinpoint task-specific and task-shared areas. Additionally, a fine-grained skill consolidation strategy protects task-specific knowledge from being forgotten while updating shared knowledge for bi-directional knowledge transfer. As a result, TaSL strikes a balance between preserving previous knowledge and excelling at new tasks. Comprehensive experiments on various backbones highlight the significant performance improvements of TaSL over existing state-of-the-art methods. The source code1 is provided for reproducibility. Copyright © 2024, The Authors. All rights reserved.

关键词： Speech recognition

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A Multi-Stream Scrambling and DNA Encoding Method Based Image Encryption

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computer Systems science & Engineering 2023年第11期47卷 1321-1347页

作者： Nashat Salih Abdulkarim Alsandi Dilovan Asaad Zebari Adel Al-Zebari Falah Y.H.Ahmed Mazin Abed Mohammed Marwan Albahar Abdulaziz Ali Albahr Information Technology Duhok Private Technical InstituteDuhokIraq Department of Computer Science College of ScienceNawroz UniversityDuhok42001Iraq Department of Information Technology Technical College of Informatics AkreDuhok Polytechnic UniversityDuhokIraq Faculty of Computing and Information Technology Sohar UniversityOman College of Computer Science and Information Technology University of AnbarAnbar31001Iraq Department of Science Umm Al Qura UniversityP.O.Box 715MeccaSaudi Arabia College of Applied Medical Sciences King Saud Bin Abdulaziz University for Health SciencesAl Ahsa31982Saudi Arabia King Abdullah International Medical Research Center Al-Ahsa36276Saudi Arabia

Information security has emerged as a key problem in encryption because of the rapid evolution of the internet and ***,the progress of image encryption techniques is becoming an increasingly serious issue and considerable *** space of the key,encryption-based low confidentiality,low key sensitivity,and easily exploitable existing image encryption techniques integrating chaotic system and DNA computing are purposing the main problems to propose a new encryption technique in this *** our proposed scheme,a three-dimensional Chen’s map and a one-dimensional Logistic map are employed to construct a double-layer image encryption *** the confusion stage,different scrambling operations related to the original plain image pixels are designed using Chen’s map.A stream pixel scrambling operation related to the plain image is ***,a block scrambling-based image encryption-related stream pixel scrambled image is *** the diffusion stage,two rounds of pixel diffusion are generated related to the confusing image for intra-image ***’s map,logistic map,and DNA computing are employed to construct diffusion operations.A reverse complementary rule is applied to obtain a new form of DNA.A Chen’s map is used to produce a pseudorandom DNA sequence,and then another DNA form is constructed from a reverse pseudorandom DNA ***,the XOR operation is performed multiple times to obtain the encrypted *** to the simulation of experiments and security analysis,this approach extends the key space,has great sensitivity,and is able to withstand various typical *** adequate encryption effect is achieved by the proposed algorithm,which can simultaneously decrease the correlation between adjacent pixels by making it near zero,also the information entropy is *** number of pixels changing rate(NPCR)and the unified average change intensity(UACI)both are very near to optimal values.

关键词： Grayscale image encryption stream scrambling-confusion DNA encoding XOR operation chaotic systems

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Differentially Private Kernel Density Estimation

arXiv

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arXiv 2024年

作者： Liu, Erzhi Hu, Jerry Yao-Chieh Reneau, Alex Song, Zhao Liu, Han Center for Foundation Models and Generative AI Department of Computer Science Northwestern University EvanstonIL60208 United States Ensemble AI San FranciscoCA94133 United States Simons Institute for the Theory of Computing UC Berkeley BerkeleyCA94720 United States Center for Foundation Models and Generative AI Department of Computer Science Department of Statistics and Data Science Northwestern University EvanstonIL60208 United States

We introduce a refined differentially private (DP) data structure for kernel density estimation (KDE) with 1, 2 and pp kernels. This new DP data structure offers not only improved privacy-utility tradeoff but also better query efficiency over prior results. Specifically, we study the mathematical problem: given a similarity function f (or DP KDE) and a private dataset X ⊂ d, our goal is to preprocess X so that for any query y ∈ d, we approximate ∑ x∈X f(x, y) in a differentially private fashion. The best previous algorithm for f(x, y) = x − y1 is the node-contaminated balanced binary tree by [Backurs, Lin, Mahabadi, Silwal, and Tarnawski, ICLR 2024]. Their algorithm requires O(nd) space and time for preprocessing with n = |X|. For any query point, the query time is α−1dlog2 n, with an error guarantee of (1 + α)-approximation and ϵ−1α−0.5d1.5Rlog1.5 n. In this paper, we use the same space and pre-processing time, improve the best previous result [Backurs, Lin, Mahabadi, Silwal, and Tarnawski, ICLR 2024] in three aspects • We reduce query time by α−1 log n factor • We improve the approximation ratio from α to 1 • We reduce the error dependence by a factor of α−0.5 From a technical perspective, our method of constructing the search tree differs from previous work [Backurs, Lin, Mahabadi, Silwal, and Tarnawski, ICLR 2024]. In prior work, for each query, the answer is split into α−1 log n numbers, each derived from the summation of log n values in interval tree countings. In contrast, we construct the tree differently, splitting the answer into log n numbers, where each is a smart combination of two distance values, two counting values, and y itself. We believe our tree structure may be of independent interest. © 2024, CC BY-NC-SA.

关键词： Differential privacy

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The Impact of Language Expressions and visual Exploration on Neurodivergent Artist Quotes in Educational Setting

The Impact of Language Expressions and Visual Exploration on...

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International Conference on Business and Industrial Research (ICBIR)

作者： Desi Indrawati Yuda Suryasa Sjaerodji Aris Darisman Imaniar Rizki Waridha Computer Science Department Language Center Faculty of Humanities Bina Nusantara University Bandung West Java Indonesia Visual Communication Design Study Program School of Design Bina Nusantara University Bandung West Java Indonesia

ISBN: (数字)9798350383027

ISBN: (纸本)9798350383034

In recent years, neurodiversity has gained popularity among those proponents of people's inclusion, dignity, and rights. Demonstrations and images help them learn more effectively. Give written instructions, visual clues, and brief spoken instructions when feasible. Furthermore, the researchers included seventeen student populations, eleven officers and staff, and twelve lecturer populations. For two days in a row, they attended the interactive quotation display by neurodivergent artists, and in response, they contributed drawings that reflected their interpretations of the quotes. An interview served as the second method of gathering data. The researchers also conducted a structured interview with four students, four officers, and three lecturers acting as spokespeople. Quotes from the works of Neurodivergent Artists such as Nintendo, Love, Amsterdam, Suzanne, Kacamata (Glasses), Teman (Friends), Mudik (Homecoming), Menjahit (Sewing), and Iggle can be found in the Interactive Installation activity. Using a mixed-methods approach, the researchers collected and examined the data (Creswell, 2014). It is an approach that blends qualitative and quantitative research techniques. According to the findings, the Amsterdam quote is liked by lecturers, staff, and students alike. In addition, the Love quote sparks curiosity in both students and instructors, indicating a mutual admiration for its meaning.

关键词： visualization Glass Semiotics Sparks Interviews Business

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MCCNet: Multi-Color Cascade Network with Weight Transfer for Single Image Depth Prediction on Outdoor Relief Images 25th

MCCNet: Multi-Color Cascade Network with Weight Transfer for...

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25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Frisky, Aufaclav Zatu Kusuma Putranto, Andi Zambanini, Sebastian Sablatnig, Robert Computer Vision Lab Institute of Visual Computing and Human-Centered Technology Faculty of Informatics TU Wien Vienna Austria Department of Computer Science and Electronics Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Yogyakarta Indonesia Department of Archaeology Faculty of Cultural Science Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (纸本)9783030687861

Single image depth prediction is considerably difficult since depth cannot be estimated from pixel correspondences. Thus, prior knowledge, such as registered pixel and depth information from the user is required. Another problem rises when targeting a specific domain requirement as the number of freely available training datasets is limited. Due to color problem in relief images, we present a new outdoor Registered Relief Depth (RRD) Prambanan dataset, consisting of outdoor images of Prambanan temple relief with registered depth information supervised by archaeologists and computer scientists. In order to solve the problem, we also propose a new depth predictor, called Multi-Color Cascade Network (MCCNet), with weight transfer. Applied on the new RRD Prambanan dataset, our method performs better in different materials than the baseline with 2.53 mm RMSE. In the NYU Depth V2 dataset, our method’s performance is better than the baselines and in line with other state-of-the-art works. © 2021, Springer Nature Switzerland AG.

关键词： Forecasting

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Preprocessing and Framework for Edge Intelligence in Air Quality Control: Work on Progress

Preprocessing and Framework for Edge Intelligence in Air Qua...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Aditya Putra Perdana Prasetyo Mohd. Yazid Idris Hanif Fakhrurroja Deris Stiawan Department of Computer Engineering Universitas Sriwijaya Palembang Indonesia Faculty of Computing Universiti Teknologi Malaysia Johor Malaysia Research Center for Smart Mechatronics National Research and Innovation Agency Bandung Indonesia Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia

ISBN: (数字)9798331533243

ISBN: (纸本)9798331533250

As urban areas face increasing challenges related to air pollution, the integration of edge computing and artificial intelligence (AI) offers a viable solution for real-time monitoring and control. This research focuses on the development of preprocessing techniques that enhance data collection and analysis at the edge, addressing critical issues such as energy consumption and data latency. By proposing a lightweight framework, the study aims to facilitate intelligent processing and data sharing in air quality applications. Additionally, the paper highlights the significance of real-time data in managing indoor air quality (IAQ) and its impact on occupant health and productivity. The ongoing work seeks to create a comprehensive framework that not only improves air quality monitoring but also incorporates predictive analytics to forecast air quality trends, thereby informing policy and operational decisions. Ultimately, this research underscores the potential of edge intelligence to transform air quality management into a proactive and adaptive system, contributing to healthier urban living environments.

关键词： Reviews Urban areas Transforms Air quality Market research Real-time systems Stakeholders Sustainable development Research and development Edge computing

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Decoupling semantic similarity from spatial alignment for neural networks 24

Decoupling semantic similarity from spatial alignment for ne...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Tassilo Wald Constantin Ulrich Gregor Köhler David Zimmerer Stefan Denner Michael Baumgartner Fabian Isensee Priyank Jaini Klaus H. Maier-Hein Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany and Helmholtz Imaging DKFZ Heidelberg Germany and Faculty of Mathematics and Computer Science University of Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany and Medical Faculty Heidelberg University of Heidelberg Germany and National Center for Tumor Diseases (NCT) Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany and Faculty of Mathematics and Computer Science University of Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany and Helmholtz Imaging DKFZ Heidelberg Germany Google Deepmind Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany and Helmholtz Imaging DKFZ Heidelberg Germany and Faculty of Mathematics and Computer Science University of Heidelberg Germany and Medical Faculty Heidelberg University of Heidelberg Germany and Pattern Analysis and Learning Group Department of Radiation Oncology

ISBN: (纸本)9798331314385

What representation do deep neural networks learn? How similar are images to each other for neural networks? Despite the overwhelming success of deep learning methods key questions about their internal workings still remain largely unanswered, due to their internal high dimensionality and complexity. To address this, one approach is to measure the similarity of activation responses to various inputs. Representational Similarity Matrices (RSMs) distill this similarity into scalar values for each input pair. These matrices encapsulate the entire similarity structure of a system, indicating which input leads to similar responses. While the similarity between images is ambiguous, we argue that the spatial location of semantic objects does neither influence human perception nor deep learning classifiers. Thus this should be reflected in the definition of similarity between image responses for computer vision systems. Revisiting the established similarity calculations for RSMs we expose their sensitivity to spatial alignment. In this paper, we propose to solve this through semantic RSMs, which are invariant to spatial permutation. We measure semantic similarity between input responses by formulating it as a set-matching problem. Further, we quantify the superiority of semantic RSMs over spatio-semantic RSMs through image retrieval and by comparing the similarity between representations to the similarity between predicted class probabilities.

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MassSpecGym: a benchmark for the discovery and identification of molecules 24

MassSpecGym: a benchmark for the discovery and identificatio...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Roman Bushuiev Anton Bushuiev Niek F. de Jonge Adamo Young Fleming Kretschmer Raman Samusevich Janne Heirman Fei Wang Luke Zhang Kai Dührkop Marcus Ludwig Nils A. Haupt Apurva Kalia Corinna Brungs Robin Schmid Russell Greiner Bo Wang David S. Wishart Li-Ping Liu Juho Rousu Wout Bittremieux Hannes Rost Tytus D. Mak Soha Hassoun Florian Huber Justin J.J. van der Hooft Michael A. Stravs Sebastian Böcker Josef Sivic Tomáš Pluskal Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences and Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Bioinformatics Group Wageningen University & Research Department of Computer Science University of Toronto Chair for Bioinformatics Institute for Computer Science Friedrich Schiller University Jena Department of Computer Science University of Antwerp Department of computing science University of Alberta and Alberta Machine Intelligence Institute Department of Molecular Genetics University of Toronto Bright Giant GmbH Department of Computer Science Tufts University Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences Department of computing science and Department of Biological Sciences University of Alberta Department of Computer Science Aalto University Mass Spectrometry Data Center National Institute of Standards and Technology Department of Computer Science and Department of Chemical and Biological Engineering Tufts University Centre for Digitalisation and Digitality University of Applied Sciences Düsseldorf Bioinformatics Group Wageningen University & Research and Department of Biochemistry University of Johannesburg Eawag: Swiss Federal Institute of Aquatic Science and Technology

ISBN: (纸本)9798331314385

The discovery and identification of molecules in biological and environmental samples is crucial for advancing biomedical and chemical sciences. Tandem mass spectrometry (MS/MS) is the leading technique for high-throughput elucidation of molecular structures. However, decoding a molecular structure from its mass spectrum is exceptionally challenging, even when performed by human experts. As a result, the vast majority of acquired MS/MS spectra remain uninterpreted, thereby limiting our understanding of the underlying (bio)chemical processes. Despite decades of progress in machine learning applications for predicting molecular structures from MS/MS spectra, the development of new methods is severely hindered by the lack of standard datasets and evaluation protocols. To address this problem, we propose MassSpecGym - the first comprehensive benchmark for the discovery and identification of molecules from MS/MS data. Our benchmark comprises the largest publicly available collection of high-quality labeled MS/MS spectra and defines three MS/MS annotation challenges: de novo molecular structure generation, molecule retrieval, and spectrum simulation. It includes new evaluation metrics and a generalization-demanding data split, therefore standardizing the MS/MS annotation tasks and rendering the problem accessible to the broad machine learning community. MassSpecGym is publicly available at https://***/pluskal-lab/MassSpecGym.

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Retraction Note: High performance reconciliation for practical quantum key distribution systems

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Optical and Quantum Electronics 2024年第12期56卷 1-2页

作者： Mao, ao-Kun Li, Qiong Hao, Peng-Lei Abd-El-Atty, Bassem Iliyasu, Abdullah M. Department of Computer Science and Technology Harbin Institute of Technology Harbin China CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Hefei China Department of Computer Science Faculty of Computers and Information Luxor University Luxor Egypt Electrical Engineering Department College of Engineering Prince Sattam Bin Abdulaziz University Al- Kharj Saudi Arabia School of Computing Tokyo Institute of Technology Yokohama Japan School of Computer Science and Technology Changchun University of Science and Technology Changchun China

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A Comprehensive Survey on Intelligent Reflecting Surfaces and Unmanned Aerial Vehicles Integration for Enhanced Communication in Massive Networks 11

A Comprehensive Survey on Intelligent Reflecting Surfaces an...

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11th International Conference on Mechatronics and Robotics Engineering, ICMRE 2025

作者： Attar, Hani Ababneh, Jafar Hafez, Mohamed Rachini, Ali Solyman, Ahmed Bahy, Ramy M. Zarqa University Faculty of Engineering Zarqa Jordan College of Engineering University of Business and Technology Jeddah21448 Saudi Arabia Zarqa University Faculty of Information Technology Cyber Security Department Zarqa Jordan INTI-IU-University Nilai Faculty of Engineering Feqs Malaysia Department of Computer Science and Information Technology Jounieh Lebanon School of Computing Engineering and Built Environment Glasgow Caledonian University Glasgow United Kingdom Technical Research Center Cairo Egypt

ISBN: (纸本)9798331509293

Intelligent Reflecting Surfaces (IRSs) offer a revolutionary approach to wireless communication by dynamically controlling the properties of electromagnetic waves. By manipulating wavefronts without requiring radio frequency links, IRSs can enhance spectrum and energy efficiency, reduce costs, and improve overall system performance. Unmanned Aerial Vehicles (UAVs) have garnered significant attention due to their mobility and adaptability. However, real-time data transmission between UAVs can be hindered by obstacles and security risks. By combining IRSs and UAVs, we can create unparalleled opportunities in demanding environments. Through coordinated movements and intelligent wave reflection, both systems can optimize wireless signal propagation. This paper provides a comprehensive review of IRS-assisted UAV communications. We explore existing research, introduce novel technologies and applications, and highlight potential research directions for developing low-cost and energy-efficient wireless systems. Additionally, we address current challenges and outline promising areas for future study. © 2025 IEEE.

关键词： Drones

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