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arXiv 2022年

作者： Samuel, Mesay Schmidt-Thieme, Lars Sharma, D.P. Sinamo, Abiot Bruck, Abey Arba Minch University Faculty of Computing and Software Engineering Ethiopia Information Systems and Machine Learning Lab Hildesheim31141 Germany Amuit Moefdre under Undp Germany Ministry of Innovation and Technology Ethiopia

Few-shot learning is an important, but challenging problem of machine learning aimed at learning from only fewer labeled training examples. It has become an active area of research due to deep learning requiring huge amounts of labeled dataset, which is not feasible in the real world. Learning from a few examples is also an important attempt towards learning like humans. Few-shot learning has proven a very good promise in different areas of machine learning applications, particularly in image classification. As it is a recent technique, most researchers focus on understanding and solving the issues related to its concept by focusing only on common image datasets like Mini-ImageNet and Omniglot. Few-shot learning also opens an opportunity to address low resource languages like Amharic. In this study, offline handwritten Amharic character recognition using few-shot learning is addressed. Particularly, prototypical networks, the popular and simpler type of few-shot learning, is implemented as a baseline. Using the opportunities explored in the nature of Amharic alphabet having row-wise and column-wise similarities, a novel way of augmenting the training episodes is proposed. The experimental results show that the proposed method outperformed the baseline method. This study has implemented few-shot learning for Amharic characters for the first time. More importantly, the findings of the study open new ways of examining the influence of training episodes in few-shot learning, which is one of the important issues that needs exploration. The datasets used for this study are collected from native Amharic language writers using an Android App developed as a part of this study. © 2022, CC BY.

关键词： Character recognition

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Ppt4J: Patch Presence Test for Java Binaries

arXiv

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arXiv 2023年

作者： Pan, Zhiyuan Hu, Xing Xia, Xin Zhan, Xian Lo, David Yang, Xiaohu The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China Software Engineering Application Technology Lab Huawei Hangzhou China The Hong Kong Polytechnic University Hong Kong Hong Kong School of Computing and Information Systems Singapore Management University Singapore

The number of vulnerabilities reported in open source software has increased substantially in recent years. Security patches provide the necessary measures to protect software from attacks and vulnerabilities. In practice, it is difficult to identify whether patches have been integrated into software, especially if we only have binary files. Therefore, the ability to test whether a patch is applied to the target binary, a.k.a. patch presence test, is crucial for practitioners. However, it is challenging to obtain accurate semantic information from patches, which could lead to incorrect results. In this paper, we propose a new patch presence test framework named Ppt4J (Patch Presence Test for Java Binaries). Ppt4J is designed for open-source Java libraries. It takes Java binaries (i.e. bytecode files) as input, extracts semantic information from patches, and uses feature-based techniques to identify patch lines in the binaries. To evaluate the effectiveness of our proposed approach Ppt4J, we construct a dataset with binaries that include 110 vulnerabilities. The results show that Ppt4J achieves an F1 score of 98.5% with reasonable efficiency, improving the baseline by 14.2%. Furthermore, we conduct an in-the-wild evaluation of Ppt4J on JetBrains IntelliJ IDEA. The results suggest that a third-party library included in the software is not patched for two CVEs, and we have reported this potential security problem to the vendor. © 2023, CC BY-NC-ND.

关键词： Open source software

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Memory and Schema in Human-Generative Artificial Intelligence Interactions

Memory and Schema in Human-Generative Artificial Intelligenc...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Dimitrios P. Panagoulias Persephone Papatheodosiou Anastasios Bonakis Dimitrios Dikeos Maria Virvou George A. Tsihrintzis Department of Informatics University of Piraeus Piraeus Greece Department of Psychiatry Sleep Research Unit National and Kapodistrian University of Athens Athens Greece Second Department of Neurology National and Kapodistrian University of Athens Athens Greece Department of Informatics Lab of Software Engineering University of Piraeus Piraeus Greece Department of Informatics Lab of Pattern Recognition and Machine Learning - Multimedia Systems University of Piraeus Piraeus Greece

ISBN: (数字)9798331527235

ISBN: (纸本)9798331527242

In this paper, we explore memory and Schema through the lens of mathematical representation. By defining themes related to cognitive processes, we propose a compression algorithm that measures and retains important information of previous (historic) user-Generative AI interaction. Time and memory are interconnected via a decay mechanism, where context gets more abstract as time passes. At the same time, memories with thematic resemblance can be structured into Schemas using set theory, based on rules influenced by a maturity threshold. This threshold is determined by factors such as criticality, emotional-user interaction, and mass, which is the measure of the summation of related memories. Our approach reconstructs memories into reusable parameters and formulates Schemas, offering a foundation for more personalized and cost-effective human-GAI interactions.

关键词： Cognitive processes Set theory Artificial intelligence Compression algorithms Lenses

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On the potentials of interaction breakdowns for HRI

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Behavioral and Brain Sciences 2023年第1期46卷 e49-e49页

作者： Wrede, Britta Vollmer, Anna-Lisa Krach, Sören Software Engineering for Cognitive Robots and Cognitive Systems University of Bremen Bremen 28359 Germany Medical Assistive Systems Bielefeld University Bielefeld 33615 Germany Department of Psychiatry and Psychotherapy Social Neuroscience Lab (SNL) LÜbeck University Center of Brain Behavior and Metabolism (CBBM) Lübeck 23538 Germany

How do we switch between playing along and treating robots as technical agents? We propose interaction breakdowns to help solve this social artifact puzzle: Breaks cause changes from fluid interaction to explicit reasoning and interaction with the raw artifact. These changes are closely linked to understanding the technical architecture and could be used to design better human-robot interaction (HRI). © The Author(s), 2023. Published by Cambridge University Press.

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Diff-Reg: Diffusion Model in Doubly Stochastic Matrix Space for Registration Problem

arXiv

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arXiv 2024年

作者： Wu, Qianliang Jiang, Haobo Luo, Lei Li, Jun Ding, Yaqing Xie, Jin Yang, Jian PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China School of Intelligence Science and Technology Nanjing University Suzhou China Visual Recognition Group Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic National University of Singapore Singapore

Establishing reliable correspondences is essential for 3D and 2D-3D registration tasks. Existing methods commonly leverage geometric or semantic point features to generate potential correspondences. However, these features may face challenges such as large deformation, scale inconsistency, and ambiguous matching problems (e.g., symmetry). Additionally, many previous methods, which rely on single-pass prediction, may struggle with local minima in complex scenarios. To mitigate these challenges, we introduce a diffusion matching model for robust correspondence construction. Our approach treats correspondence estimation as a denoising diffusion process within the doubly stochastic matrix space, which gradually denoises (refines) a doubly stochastic matching matrix to the ground-truth one for high-quality correspondence estimation. It involves a forward diffusion process that gradually introduces Gaussian noise into the ground truth matching matrix and a reverse denoising process that iteratively refines the noisy one. In particular, we deploy a lightweight denoising strategy during the inference phase. Specifically, once points/image features are extracted and fixed, we utilize them to conduct multiple-pass denoising predictions in the reverse sampling process. Evaluation of our method on both 3D and 2D-3D registration tasks confirms its effectiveness. The code is available at https://***/wuqianliang/Diff-Reg. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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Multi-script handwritten digit recognition using multi-task learning

arXiv

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arXiv 2021年

作者： Gondere, Mesay Samuel Schmidt-Thieme, Lars Sharma, Durga Prasad Scholz, Randolf Arba Minch University Faculty of Computing and Software Engineering Ethiopia Information Systems and Machine Learning Lab Hildesheim31141 Germany

Handwritten digit recognition is one of the extensively studied area in machine learning. Apart from the wider research on handwritten digit recognition on MNIST dataset, there are many other research works on various script recognition. However, it is not very common for multi-script digit recognition which encourage the development of robust and multipurpose systems. Additionally working on multi-script digit recognition enables multi-task learning, considering the script classification as a related task for instance. It is evident that multi-task learning improves model performance through inductive transfer using the information contained in related tasks. Therefore, in this study multi-script handwritten digit recognition using multi-task learning will be investigated. As a specific case of demonstrating the solution to the problem, Amharic handwritten character recognition will also be experimented. The handwritten digits of three scripts including Latin, Arabic and Kannada are studied to show that multi-task models with reformulation of the individual tasks have shown promising results. In this study a novel way of using the individual tasks predictions was proposed to help classification performance and regularize the different loss for the purpose of the main task. This finding has outperformed the baseline and the conventional multi-task learning models. More importantly, it avoided the need for weighting the different losses of the tasks, which is one of the challenges in multi-task learning. © 2021, CC BY.

关键词： Learning systems

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Optimal Resource Utilization in Hyperledger Fabric: A Comprehensive SPN-Based Performance Evaluation Paradigm

Optimal Resource Utilization in Hyperledger Fabric: A Compre...

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IEEE Symposium on Network Operations and Management

作者： Carlos Melo Glauber Gonçalves Francisco A. Silva Leonel Feitosa Iure Fé André Soares Eunmi Choi Tuan Anh Nguyen Dugki Min Applied Research on Distributed Systems Lab (PASID) Federal University of Piauí (UFPI) Brazil School of Software College of Computer Science Kookmin University Seoul South Korea Konkuk Aerospace Design-Airworlhiness Research Inslilule (KADA) Konkuk Universily Seoul Soulh Korea Department of Computer Science and Engineering Konkuk University Seoul South Korea

ISBN: (数字)9798350327939

ISBN: (纸本)9798350327946

Hyperledger Fabric stands as a leading framework for permissioned block-chain systems, ensuring data security and audit-ability for enterprise applications. As applications on this platform grow, understanding its complex configuration concerning various block-chain parameters becomes vital. These configurations significantly affect the system’s performance and cost. In this research, we introduce a Stochastic Petri Net (SPN) model to analyze Hyper-ledger Fabric’s performance, considering variations in block-chain parameters, computational resources, and transaction rates. We provide case studies to validate the utility of our model, aiding block-chain administrators in determining optimal configurations for their applications. A key observation from our model highlights the block size’s role in system response time. We noted an increased mean response time, between 1 to 25 seconds, due to variations in transaction arrival rates.

关键词： Performance evaluation Distributed ledger Computational modeling Data security Petri nets Stochastic processes Fabrics

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Unsupervised Detailed Human Shape Estimation from Multi-view Color Images 11th

Unsupervised Detailed Human Shape Estimation from Multi-view...

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11th International Conference on Image and Graphics, ICIG 2021

作者： Zheng, Huayu Wang, Kangkan Li, Wei Yang, Jian Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Nanjing University of Science and Technology Nanjing China Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China State Key Lab for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9783030873578

This paper presents a novel framework to estimate detailed human body shape from color images in an unsupervised manner. It is a challenging task due to factors such as variations in human shapes, occlusion, and cloth details. The existing methods are mainly supervised and require a large number of ground truth real training data which is usually hard to obtain. To solve this problem, we propose an unsupervised detailed human shape estimation method from multi-view color images. Specifically, we first predict the depth map for the source view through robust photometric consistency with different views. Then, we predict the initial SMPL model from the color image and refine it by an iterative error feedback regressor based on point clouds of the predicted depth map. Finally, the refined SMPL model is deformed to fit the details (i.e., clothes and faces) on the point clouds to recover the detailed human shapes which are represented by adding a set of offsets to the SMPL model. The experimental results on different dataset demonstrate that our method outperforms the state-of-the-art methods and achieves higher reconstruction accuracy. © 2021, Springer Nature Switzerland AG.

关键词： Iterative methods

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Multi-mode systems for Resilient Security in Industry 4.0

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Procedia Computer Science 2021年 180卷 301-307页

作者： Michael Riegler Johannes Sametinger LIT Secure and Correct Systems Lab and Dept. of Business Informatics - Software Engineering Johannes Kepler University Linz Altenberger Straβe 69 4040 Linz Austria

In the era of the Internet of Things and Industry 4.0, machines and devices are increasingly getting connected. These connections go hand in hand with security vulnerabilities and potential threats to these devices. In regular IT systems, we typically provide updates to eliminate vulnerabilities. In industrial automation and control systems, especially in mass production, legacy systems are widespread and installing updates causes downtime. Availability is one of the top goals; stopping a machine in case of a cyber-security threat is often too expensive. But, system integrators and asset owners should not have to wait until product or component suppliers release appropriate updates. Due to safety and warranty requirements, developing and distributing updates can take a long time. In the meantime, attackers can pose threats by taking advantage of devices’ known vulnerabilities. In this paper, we propose the design of resilient systems based on multi-modal architectures with several operational modes. When vulnerabilities of systems become known, or when systems get even attacked at some point, mode switching can overcome the time between vulnerability disclosure or attack, and the availability of corresponding security patches. Therefore, system integrators and asset owners can actively protect themselves by implicitly or explicitly switching to modes with reduced attack surfaces and, thus, with limited ranges of activity for attackers.

关键词： Multi-mode systems Mode switching Resilience Security Industry 4.0 Zero-day vulnerabilities

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Tighter Bounds of Speedup Factor of Partitioned EDF for Constrained-Deadline Sporadic Tasks 42

Tighter Bounds of Speedup Factor of Partitioned EDF for Cons...

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42nd IEEE Real-Time systems Symposium, RTSS 2021

作者： Liu, Xingwu Chen, Zizhao Han, Xin Sun, Zhenyu Guo, Zhishan School of Mathematical Sciences Dalian University of Technology China SK-Lab of Media Convergence Production Technology and Systems Chinaso Inc School of Software Technology Dalian University of Technology China SK-Lab of Computer Architecture ICT CAS University of CAS Beijing China Department of Electrical and Computer Engineering University of Central Florida United States

ISBN: (纸本)9781665428026

Even though earliest-deadline-first (EDF) is optimal in terms of uniprocessor schedulability, it is co-NP-hard to precisely verify uniprocessor schedulability for constrained-deadline task sets. The most efficient way to solve this problem in polynomial time is via a partially linear approximation of the demand bound function. Such approximation leads to a simple uniprocessor schedulability testing with speedup factor ρ. Such a result further leads to Deadline-Monotonic Partitioned-EDF on multi-processors with speedup factor of 1 + ρ − 1/m (where m is the number of processors). The current state of the art results indicate that ρ is within the range [1.5, 14/9]. Especially, it has been a conjecture that ρ = 1.5. This paper improves the range of ρ to (1.5026, 1.5380). The improved lower bound disproves the conjecture of lower bound 1.5. A novel technique is to construct an auxiliary function that is larger than the approximate demand bound function but keeps the supremum ρ unchanged. It solves the dilemma that beating the lower bound 1.5 requires extremely large task sets, while the large size makes it difficult to check the schedulability. This technique not only enables us to disprove 1.5 by a task set of only eight tasks, but also sheds light on future work in transferring/downsizing task sets and deriving utilization bound based tests for various workload abstraction models, such as DAG tasks. ©2021 IEEE

关键词： Polynomial approximation

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