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检索条件"丛书名=Lecture Notes in Computer Science"

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Bounded-Ratio Gapped String Indexing 31st

Bounded-Ratio Gapped String Indexing

引用

31st International Symposium on String Processing and Information Retrieval (SPIRE)

作者： Ganguly, Arnab Gibney, Daniel MacNichol, Paul Thankachan, Sharma V. Univ Wisconsin Whitewater Whitewater WI USA Univ Texas Dallas Dallas TX 75390 USA North Carolina State Univ Raleigh NC USA

ISBN: (纸本)9783031721991;9783031722004

In the gapped string indexing problem, one is given a text T[1.. n] to preprocess. At query time, a gapped pattern P = P-1[alpha.. beta]P-2 and an integer range [alpha.. beta] are provided, where P-1 and P-2 are strings of total length m. The goal of the query is to report all pairs of occurrences of P-1 and P-2 with a gap falling within [alpha.. beta]. An existing (conditional) lower bound reveals that any index with query time (O) over tildem + occ) must occupy almost quadratic space, where occ is the output size. However, there are interesting special cases where more efficient solutions are possible. For example, queries with a bounded gap, i.e., beta <= G (fixed at construction) can be answered optimally using an (O) over tilde( nG) space structure. In this paper, we bring out an interesting version of the problem where rather than having a fixed upper bound on beta, we fix gamma and allow any beta <= gamma center dot m (i.e., allow longer gaps for longer patterns;gap-to-pattern ratio is bounded). We show that such queries can be answered optimally using an (O) over tilde (n gamma) space structure.

关键词： Indexing (of information)

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Playing Games on Automata 22nd

Playing Games on Automata

引用

22nd International Symposium on Automated Technology for Verification and Analysis

作者： Kupferman, Orna Hebrew Univ Jerusalem Sch Engn & Comp Sci Jerusalem Israel

ISBN: (纸本)9783031787089;9783031787096

The interaction between a system and its environment corresponds to a game in which the system and the environment generate a word over the alphabet of assignments to the input and output signals. The system player wins if the generated word satisfies a desired specification. A correct reactive system has to satisfy its specification in all environments, and thus corresponds to a winning strategy for the system player in the above game. This view is the key to the game-based approach for reactive synthesis. It reduces synthesis to the problem of generating winning strategies in two-player games whose winning conditions are on-going behaviors, which can be specified by automata on infinite words. The paper presents the game-based approach, focusing on ways to cope with the fact that the game cannot be played over nondeterministic automata.

关键词： Automata theory

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Voices of Asynchronous Learning Students: Revealing Learning Characteristics Through Vocabulary Analysis of notes Tagged in Videos 10th

Voices of Asynchronous Learning Students: Revealing Learning...

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29th International Conference on Database Systems for Advanced Applications (DASFAA)

作者： Wang, Xiaonan Su, Yancong Sun, Yi Nishida, Takeshi Ohtsuki, Kazuhiro Kiyomitsu, Hidenari Kobe Univ Grad Sch Intercultural Studies Kobe Hyogo Japan Xiamen Univ Technol Sch Design & Art Xiamen Peoples R China Grad Sch Informat Technol Kobe Inst Comp Kobe Hyogo Japan

ISBN: (纸本)9789819609130;9789819609147

This paper describes a method for analyzing learning data from video courses. The data comes from an on-demand introductory programming course at a university. The study analyzes differences in note content characteristics across students by exploring patterns of student notes in a video learning environment, combining quantitative analysis with qualitative analysis centered on the vocabulary used in student notes. By deploying a custom designed learning support system, we facilitated the straightforward expression of students' questions and notes, thereby collecting rich data reflecting their learning process. Initial findings suggest that the frequency and distribution of specific vocabulary used in students' notes provide insights into the range of learners' interests and depth of understanding. For example, although different students recorded notes on the same topic at a specific point in a video, there were significant differences in their focus and note content. Some students tended to record how-to's and specific features, while others focused more on theoretical concepts and programming principles. These findings show that individual student differences significantly influence their learning focus and information-processing style in a video learning environment. This analysis method allows educators to target instructional interventions based on learners' unique characteristics of engagement and comprehension as demonstrated through vocabulary use. The preliminary results of this study provide educators with insights to help them understand learner diversity in digital learning environments, providing an essential basis for personalized lesson design and improved learning outcomes.

关键词： Asynchronous Learning Learning Strategy Learner Characteristic

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SC-WGAN: GAN-Based Oversampling Method for Network Intrusion Detection 28th

SC-WGAN: GAN-Based Oversampling Method for Network Intrusion...

引用

28th International Conference on Engineering of Complex computer Systems (ICECCS)

作者： Bai, Wuxia Wang, Kailong Chen, Kai Li, Shenghui Li, Bingqian Zhang, Ning Huazhong Univ Sci & Technol Wuhan 430074 Peoples R China

ISBN: (纸本)9783031664557;9783031664564

The growing cyber threat landscape necessitates robust defenses, with Network Intrusion Detection Systems (NIDS) at the forefront. Leveraging Deep Neural Networks (DNN) has significantly improved detection accuracy in NIDS. Nonetheless, the inherent data imbalance between malicious and normal network traffic impairs the efficacy of DNN-based methods. Traditional approaches employ Generative Adversarial Networks (GANs) to mitigate this by generating minority class samples. However, these methods often struggle with the scarcity of specific data types during training, leading to low-quality synthetic samples and sub-optimal detection performance. Addressing this, we introduce the Synchronous Classifier Wasserstein Generative Adversarial Network (SC-WGAN). This novel model extends the WGAN framework by integrating a classifier that processes all traffic data types. This classifier collaborates with the discriminator during the training process, guiding the generator to produce higher-quality synthetic samples. We evaluate SC-WGAN's performance on three well-known open-source benchmark datasets. Additionally, we compare it against contemporary GAN-based solutions tackling data imbalance. Our findings reveal that SC-WGAN, surpasses existing methods in generating more representative samples and enhancing NIDS detection accuracy.

关键词： Network Intrusion Detection Imbalanced Data Oversampling GAN

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From Coarse to Fine: A Novel Colon Polyp Segmentation Method Like Human Observation 7th

From Coarse to Fine: A Novel Colon Polyp Segmentation Method...

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7th Chinese Conference on Pattern Recognition and computer Vision

作者： Wang, Wei Sun, Huiying Wang, Xin Changsha Univ Sci & Technol Sch Comp & Commun Engn Changsha Peoples R China

ISBN: (纸本)9789819784950;9789819784967

Colon polyp screening is critical for the prevention of colon cancer, and the use of colon polyp segmentation to assist physicians in identifying potential polyps can improve detection efficiency and reduce misdiagnosis and missed diagnoses. However, polyp segmentation encounters the following challenges: (1) the size and shape of polyps vary widely;(2) the edge between polyps and the surrounding normal area is not obvious. To address the above challenges, a novel colon polyp segmentation method like human observation (LHONet) is proposed. This approach aims to align the polyp segmentation network more closely with human cognitive processes. First, the rough outline of the colon polyp image is identified to roughly understand the size and shape of the polyp, and then the polyp edge is finely segmented. The network structure consists of three modules: the Rough Outline Generation (ROG) module is designed to generate the rough outline of colon polyps;the Edge Information Extraction (EIE) module extracts the edge information of the polyps more accurately by combining with the classical edge detection technique;and the Outline Feature Clarifying (OFC) module is devised to supplement the edge information into the rough outline to realize the accurate segmentation of polyps. The method was compared to other methods on five datasets: EndoScene, CVC-ClinicDB, KvasirSEG, CVC-ColonDB, and ETIS-LaribPolypDB, with mDice scores of 90.79, 94.46, 92.13, 82.00, 82.29%, respectively. The codes are available at https://***/heyeying/LHONet.

关键词： Polyps Rough outline Clarify Edge information

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Serious Practices for Interactive Waste Sorting Mini-game 10th

Serious Practices for Interactive Waste Sorting Mini-game

引用

10th Joint International Conference on Serious Games

作者： Sun, Qiming Hsiao, I-Han Santa Clara Univ Santa Clara CA 95053 USA

ISBN: (纸本)9783031741371;9783031741388

Effective waste management is crucial for sustainable living, but many individuals find it challenging to navigate the complexities of waste classification. This study presents a web-based serious game that utilizes interactive sorting quizzes, created by both users and AI, to promote environmental sustainability learning. The game incorporates AI-generated feedback, a carbon credit system, and user-generated content to engage and educate participants. Two user studies involving 48 university students were conducted to evaluate the game's effectiveness. The findings suggest that the game effectively promotes learning and improves participants' understanding of sustainable waste management practices. The results highlight the potential of serious games to encourage environmental education and sustainable behaviors, particularly when they incorporate user agency and community involvement. Using emerging technologies and engaging users, serious games can serve as valuable tools to promote sustainable practices and address environmental challenges.

关键词： Environmental sustainability Waste management Interactive learning Distributed practices

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Temporal Evaluation of Uncertainty Quantification Under Distribution Shift 1st

Temporal Evaluation of Uncertainty Quantification Under Dist...

引用

1st International Workshop on AI in Drug Discovery (AIDD)

作者： Svensson, Emma Friesacher, Hannah Rosa Arany, Adam Mervin, Lewis Engkvist, Ola Johannes Kepler Univ Linz Inst Machine Learning ELLIS Unit Linz A-4040 Linz Austria Katholieke Univ Leuven ESAT STADIUS B-3000 Leuven Belgium AstraZeneca Gothenburg R&D Discovery Sci Mol AI S-43183 Molndal Sweden AstraZeneca Cambridge R&D Discovery Sci Mol AI Cambridge CB2 0AA England Chalmers Univ Technol Dept Comp Sci & Engn S-41296 Gothenburg Sweden

ISBN: (纸本)9783031723803;9783031723810

Uncertainty quantification is emerging as a critical tool in high-stakes decision-making processes, where trust in automated predictions that lack accuracy and precision can be time-consuming and costly. In drug discovery, such high-stakes decisions are based on modeling the properties of potential drug compounds on biological assays. So far, existing uncertainty quantification methods have primarily been evaluated using public datasets that lack the temporal context necessary to understand their performance over time. In this work, we address the pressing need for a comprehensive, large-scale temporal evaluation of uncertainty quantification methodologies in the context of assay-based molecular property prediction. Our novel framework benchmarks three ensemble-based approaches to uncertainty quantification and explores the effect of adding lower-quality data during training in the form of censored labels. We investigate the robustness of the predictive performance and the calibration and reliability of predictive uncertainty by the models as time evolves. Moreover, we explore how the predictive uncertainty behaves in response to varying degrees of distribution shift. By doing so, our analysis not only advances the field but also provides practical implications for real-world pharmaceutical applications.

关键词： uncertainty quantification temporal evaluation distribution shift deep learning drug discovery molecular property prediction

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Automated Flaw Detection for Industrial Robot RESTful Service 26th

Automated Flaw Detection for Industrial Robot RESTful Servic...

引用

26th International Conference on Verification Model Checking and Abstract Interpretation

作者： Wang, Yuncheng Liu, Puzhuo Zheng, Yaowen Fang, Dongliang Si, Shuaizong Pan, Zhiwen Zhang, Weidong Sun, Limin Chinese Acad Sci Inst Informat Engn Beijing Key Lab IOT Informat Secur Technol Beijing Peoples R China Univ Chinese Acad Sci Sch Cyber Secur Beijing Peoples R China Tsinghua Univ Beijing Peoples R China

ISBN: (纸本)9783031827020;9783031827037

As industrial robots become an integral part of Industry 4.0 in the manufacturing sector, their interconnection and interoperability introduce significant security challenges. RESTful Web services have emerged as the preferred method for network communication due to their simplicity and ease of use. However, the effective detection of security flaws in RESTful services for industrial robots still faces three key challenges: high-quality test case generation, high-throughput testing, and anomaly detection. Unlike traditional applications deployed within cloud services, limited computational resources, unique controller states, and unclear API specifications in robots further complicate the resolution of these challenges. Consequently, a large number of security flaws persist in real and deployed devices, with some flaws even posing the risk of physical damage. To address these challenges, we propose a novel testing technique named RobRest specifically designed for emerging RESTful services in the context of robotic systems. In test case generation, RobRest analyzes description fields extracted from the OpenAPI specification, ensuring the generation of high-quality test cases. During abnormality observation, RobRest combines both cyber and physical space states to identify anomalies in the target service. Additionally, RobRest automatically customizes each testing request to the service, minimizing resource usage within the robot controller and bypassing the quantity restrictions present in the controller. Applying RobRest to industrial robots, we identified a total of 19 system flaws (4 vulnerabilities and 15 bugs), and 2 of them have been assigned CVE IDs. Exploiting them can affect a multitude of industrial robots in the physical world.

关键词： Industrial robots

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HELIOPOLIS: Verifiable Computation over Homomorphically Encrypted Data from Interactive Oracle Proofs is Practical 30th

HELIOPOLIS: Verifiable Computation over Homomorphically Encr...

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30th International Conference on the Theory and Application of Cryptology and Information Security

作者： Aranha, Diego F. Costache, Anamaria Guimaraes, Antonio Soria-Vazquez, Eduardo Aarhus Univ Aarhus Denmark NTNU Trondheim Norway IMDEA Software Inst Madrid Spain Technol Innovat Inst Abu Dhabi U Arab Emirates

ISBN: (纸本)9789819609345;9789819609352

Homomorphic encryption (HE) enables computation on encrypted data, which in turn facilitates the outsourcing of computation on private data. However, HE offers no guarantee that the returned result was honestly computed by the cloud. In order to have such guarantee, it is necessary to add verifiable computation (VC) into the system. The most efficient recent works in VC over HE focus on verifying operations on the ciphertext space of the HE scheme, which usually lacks the algebraic structure that would make it compatible with existing VC systems. For example, multiplication of ciphertexts in the current most efficient HE schemes requires non-algebraic operations such as real division and rounding. Therefore, existing works for VC over HE have to either give up on those efficient HE schemes, or incur a large overhead (an amount of constraints proportional to the ciphertext ring's size) in order to emulate these non-algebraic operations. In this work, we move away from that paradigm by placing the verification checks in the plaintext space of HE, all while the prover remains computing on ciphertexts. We achieve this by introducing a general transformation for Interactive Oracle Proofs (IOPs) to work over HE, whose result we denote as HE-IOPs. We apply this same transformation to the FRI [Ben-Sasson et al., ICALP 2018] IOP of proximity and we show how to compile HE-Reed Solomon-encoded IOPs and HE-d-correlated-IOPs with HE-FRI into HE-IOPs. Furthermore, our construction is compatible with a prover that provides input in zero-knowledge, and only relies on building blocks that are plausibly quantum-safe. Aligning the security parameters of HE and FRI is a difficult task for which we introduce several optimizations. We demonstrate their efficiency with a proof-of-concept implementation and show that we can run FRI's commit phase for 4096 encrypted Reed Solomon codewords with degree bound 2(11) in just 5.4 s (using 32 threads) on a *** instance using less than 4GB of

关键词： Reed-Solomon codes

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Local Reactivation for Communication Efficient Federated Learning Based on Sparse Gradient Deviation 7th

Local Reactivation for Communication Efficient Federated Lea...

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7th Chinese Conference on Pattern Recognition and computer Vision

作者： Mu, Chang Zhang, Ziyang Tian, Xiang Guo, Kailing Xu, Xiangmin South China Univ Technol Guangzhou 510641 Peoples R China Pazhou Lab Guangzhou 510330 Peoples R China Hefei Comprehens Natl Sci Ctr Inst Artificial Intelligence Hefei 230088 Peoples R China

ISBN: (纸本)9789819785049;9789819785056

Communication volume is a critical bottleneck restricting federated learning efficiency. Pruning is commonly employed to address this problem. To enhance the expressive ability of the pruned models, parameter reactivation which restores the training parameters of the pruned model is proposed. Compared to global server reactivation methods, local client parameter reactivation shows great potential for improvement in highly heterogeneous scenarios. However, current methods employ the same reactivation ratio across different clients, resulting in excessive reactivation in some clients and insufficient reactivation in others. We propose a local reactivation method based on sparse gradients according to the remaining parameters after pruning, using a randomly sampled mini-batch of data. The reactivation ratio for each client is determined by the deviation degree between the sparse gradients and the complete gradients. Assigning a greater reactivation ratio to a client with a greater deviation degree allow the pruned model to better approximate the complete model. The experimental results on image recognition datasets MNIST, CIFAR-10, and CIFAR-100 show our superior performance compared to the baseline method under the same uploading bandwidth constraints.

关键词： Federated learning Pruning Local reactivation

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