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检索条件"任意字段=19th International Conference on Logic Programming"

共 2639 条记录，以下是201-210 订阅

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A Simulated Annealing Meta-heuristic for Concept Learning in Description logics 1

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30th international conference on Inductive logic programming (ILP) held as part of the 1st international Joint conference on Learning and Reasoning (IJCLR)

作者： Westphal, Patrick Vahdati, Sahar Lehmann, Jens Fraunhofer Inst Intelligent Anal & Informat Syst Dresden Germany Inst Appl Informat Leipzig Germany Univ Bonn Bonn Germany

ISBN: (数字)9783030974541

ISBN: (纸本)9783030974541;9783030974534

Ontologies - providing an explicit schema for underlying data - often serve as background knowledge for machine learning approaches. Similar to ILP methods, concept learning utilizes such ontologies to learn concept expressions from examples in a supervised manner. this learning process is usually cast as a search process through the space of ontologically valid concept expressions, guided by heuristics. Such heuristics usually try to balance explorative and exploitative behaviors of the learning algorithms. While exploration ensures a good coverage of the search space, exploitation focuses on those parts of the search space likely to contain accurate concept expressions. However, at their extreme ends, both paradigms are impractical: A totally random explorative approach will only find good solutions by chance, whereas a greedy but myopic, exploitative attempt might easily get trapped in local optima. To combine the advantages of both paradigms, different meta-heuristics have been proposed. In this paper, we examine the Simulated Annealing meta-heuristic and how it can be used to balance the exploration-exploitation trade-off in concept learning. In different experimental settings, we analyse how and where existing concept learning algorithms can benefit from the Simulated Annealing meta-heuristic.

关键词： Inductive logic programming (ILP) Description logic (DL) Concept Learning (CL) Meta-heuristics

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Triple Extraction of Knowledge Graphs with DGWPN 23

Triple Extraction of Knowledge Graphs with DGWPN

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23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Song, Yipei Lin, Rongheng Zou, Hua Beijing University of Posts and Telecommunications State Key Lab of Networking and Switching Technology Beijing100876 China

ISBN: (纸本)9781665494571

Information extraction aims to provide required high-quality RDF triples for knowledge graph which is the basis of knowledge construction. the current two mainstream methods include a joint model concentrates on using deep learning to extract entities and relationships and a pipeline model based on sequential extraction. the joint method will be limited by the number of parameters and the types of parameters, this will lead to the loss of calculation results. In the pipeline model, the result of entity extraction needs to be substituted into the relationship classification, and this usually causes the interference of redundant entities to the relationship classification. For the joint training model, in the training process, entities and relationships are extracted at the same time. the results of extractions are continuously transmitted to each other during training and influence each other. If a certain parameter limit is deleted during the extraction of one type of result, the extraction result of the other side will also be deleted of the same type, which will eventually cause some results to be lost. For the pipeline model, if entities are first extracted, then relations are classified. In the process of entity extraction, invalid entity pairs with no matching relationship will be generated. this causes the convolution training speed to slow down. In this paper, in order to solve such problems in entity and relationship extraction, we propose an entity relationship extraction model includes Dilated Gate unit convolutional layers with Weight Pointer Networks, named this structure as DGWPN. this is helpful to obtain more receptive fields and multiple triples models. the advantages of our model are demonstrated through the comparison of multiple groups of experiments. the experimental results show that our method outperforms other current different baseline models on the SKE and CHIP data sets, about 5.3% higher than the current mainstream Bi-LSTM with CRF model o

关键词： Training Knowledge engineering Deep learning Pipelines Interference logic gates Information retrieval

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A Highly Efficient Profiled Power Analysis Attack Based on Power Leakage Fitting 23

A Highly Efficient Profiled Power Analysis Attack Based on P...

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作者： Li, Yuanzhi Xu, Shanshan Luo, Yuling Qin, Sheng Zhang, Shunsheng Su, Min School of Electronic Engineering Guangxi Normal University Guilin China Guangxi Asean Technology Transfer Center Nanning China

ISBN: (纸本)9781665494571

Power Analysis Attack (PAA) is one of the most effective Side Channel Attack (SCA) methods with good effect. A highly efficient profiled power analysis attack method named PLF is proposed in this paper. Nine average power traces are calculated according to the Hamming Weight (HW), and the Points of Interest (POIs) are extracted. then the template is established by linear fitting. the information hidden in the attack traces is mapped to the points in the two-dimensional coordinate system, then the correct key is cracked by calculating the distance between the points and the line. the numerical problems caused by the irreversible covariance matrix and exponential operation of Template Attack (TA) are avoided in the PLF. the PLF is verified by attacking the Advanced Encryption Standard (AES) on the Atmel XMEGA128-D4 microcontroller. the experimental results show that the computational complexity is reduced in PLF compared to TA and Correlation Power Analysis (CPA), and the slope of PLA is 95.5% and 55.1% lower than TA and CPA respectively. Besides, the PLF requires fewer power traces to effectively crack the correct key, and it has a lower Partial Guessing Entropy (PGE). Moreover, the distinguishing level of PLF is 51% and 30% higher than TA and CPA respectively. Meanwhile, PLF only needs 17 attack traces to achieve 80% Partial Success Rate (PSR), which is 57.5% and 77.9% lower than CPA and TA in the number of attack traces, respectively. © 2021 IEEE.

关键词： Power demand Microcontrollers Smart cities Fitting Side-channel attacks Programmable logic arrays Covariance matrices

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Organs-At-Risk Segmentation in Medical Imaging Based on the U-Net with Residual and Attention Mechanisms 23

Organs-At-Risk Segmentation in Medical Imaging Based on the ...

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作者： Lin, Xiao-Wei Li, Ni Qi, Qi School of Computer Science and Technology Hainan University Haikou China School of Mathematics and Statistics Hainan Normal University Hainan Normal University Key Laboratory of Data Science and Intelligence Education of Ministry of Education Haikou China

ISBN: (纸本)9781665494571

In this paper, we proposed a new organs-at-risk segmentation method for Medical images of heads and necks based on the U-Net with residuals and attention mechanism. A Project & Excite (PE) block combined with a residual method is proposed as Residual-PE Block in the U-Net encoding stage in order to enhance the feature expression ability. Attention Gates (AGs) are introduced in the decoding stage to increase the relevance of feature weighting in accord with segmentation tasks. the proposed method has been evaluated through a set of real world medical images including 22 organs at risk in the head and neck. Experimental results showed that our proposed method improved the average segmentation accuracy by 3-4% compared with current existing methods. the average Dice Similarity Coefficient (DSC) score on the segmentation of the 22 types of head-and-neck related organs at risk is 79.5% and the average 95% Hausdorff Distance (HD) is 6.99mm. It demonstrates that this approach is promising for clinical doctors to improve their accuracy and efficiency in radiotherapy. © 2021 IEEE.

关键词： Image segmentation Head three-dimensional displays Smart cities Medical services logic gates Encoding

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A Contextualized Government Service Chatbot for Individuals with limited Information Literacy 19th

A Contextualized Government Service Chatbot for Individuals ...

引用

19th international conference on Wisdom, Well-Being, Win-Win, iconference 2024

作者： Lian, Zhixuan Huang, Meiyin Wang, Fang Nankai University Tianjin300071 China

ISBN: (纸本)9783031578496

Improving the Q&A ability of government service chatbots (GSCs) has become an important issue. In practice, a large number of users with poor information literacy often pose vague questions, which makes it challenging for GSCs to comprehend their inquiries within a specific context. In order to enhance contextualization, this study has constructed a multi-turn dialogue model that incorporates R-GCN and fuzzy logic to base on the "question-answer-context" matching process. To obtain more accurate context, we propose a re-question mechanism to further press for contextual details. Additionally, we introduce the sub-graph matching mechanism of fuzzy logic and R-GCN to improve the accuracy of implicitly representation of Chinese logic in the contextualized matching process. this mechanism allows us to prune the context-irrelevant parts in the "answer" and obtain more complete context information. We collected over 300,000 words of real cases as the test-set. the results of the experiments show that this model can significantly improve the contextualized reasoning ability of GSCs in a more humanized way. the innovative response generation method in this research, which utilizes "question-answer-context" matching, is more suitable for complex scenarios where the user may not be articulate. It helps to lower the barrier for accessing government services and provides more user-friendly assistance to individuals with limited information literacy. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Fuzzy logic

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11th international conference on Industrial Engineering and Applications-Europe, ICIEA-EU 2024

11th International Conference on Industrial Engineering and ...

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11th international conference on Industrial Engineering and Applications-Europe, ICIEA-EU 2024

ISBN: (纸本)9783031581120

the proceedings contain 19 papers. the special focus in this conference is on Industrial Engineering and Applications-Europe. the topics include: Determination of Skilled Worker Requirements for Maintenance Departments Under Stochastic Failure Mode Conditions;empirical Findings on the Current State of Industrial Production Management Systems in the Context of Increasing Digitalization;process Improvement of Taping for an Assembly Electrical Wiring Harness;use of Artificial Intelligence in Occupational Health and Safety in Construction Industry: A Proposed Framework for Saudi Arabia;path Score Based Approach for Deriving Machine Sequence in Multistage Process;a Traffic Signal Timing Model with Consideration on Road Configurations, Phase Planning, and Conflict Points at a Signalized T-Intersection Road;lateral Stability Control for Four Independent Wheel Vehicles Considering the Surrounding Condition;design of an Interactive Scheduling Heuristic-Based Application;a New Data-Driven Modelling Framework for Moisture Content Prediction in Continuous Pharmaceutical Tablet Manufacturing;solving the Car Sequencing Problem with Cross-Ratio Constraints Using Constraint programming Approach;picking Optimization in U-Shaped Corridors with a Movable Depot;sustainable and Energy-Efficient Industrial Systems: Modelling the Environmental Impact of Logistics Facilities;zero-Inflated Poisson Tensor Factorization for Sparse Purchase Data in E-Commerce Markets;Hybrid Predictive Modeling for Automotive After-Sales Pricing: Integrating BiLSTM-Attention and Fuzzy logic;full-Length Hardness Prediction in Wire Rod Manufacturing Using Semantic Segmentation of thermal Images;industrial Object Detection: Leveraging Synthetic Data for Training Deep Learning Models;a Multi-step Approach for Identifying Unknown Defect Patterns on Wafer Bin Map.

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Rediscovering Argumentation Principles Utilizing Collective Attacks 19

Rediscovering Argumentation Principles Utilizing Collective ...

引用

19th international conference on Principles of Knowledge Representation and Reasoning, KR 2022

作者： Dvořák, Wolfgang König, Matthias Ulbricht, Markus Woltran, Stefan TU Wien Institute of Logic and Computation Austria Leipzig University Department of Computer Science Germany

ISBN: (纸本)9781956792010

Argumentation Frameworks (AFs) are a key formalism in AI research. their semantics have been investigated in terms of principles, which define characteristic properties in order to deliver guidance for analysing established and developing new semantics. Because of the simple structure of AFs, many desired properties hold almost trivially, at the same time hiding interesting concepts behind syntactic notions. We extend the principle-based approach to Argumentation Frameworks with Collective Attacks (SETAFs) and provide a comprehensive overview of common principles for their semantics. Our analysis shows that investigating principles based on decomposing the given SETAF (e.g. directionality or SCC-recursiveness) poses additional challenges in comparison to usual AFs. We introduce the notion of the reduct as well as the modularization principle for SETAFs which will prove beneficial for this kind of investigation. We then demonstrate how our findings can be utilized for incremental computation of extensions and give a novel parameterized tractability result for verifying preferred extensions. © 19th international conference on Principles of Knowledge Representation and Reasoning, KR 2022. All rights reserved.

关键词： Semantics

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Designing Village Idea Lab as Digital-based Incubator of Ideas and Innovation in Efforts to Establish New Entrepreneurs on Village Youth in East Java 19

Designing Village Idea Lab as Digital-based Incubator of Ide...

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19th international conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Siswanto, Ely Takada, Asako Kurniawan, Dediek Tri Prasasti, Arum Fachrunnisa, Rifka Setyono, Langgeng Universitas Negeri Malang Department of Management Malang Indonesia Hosei University Hosei Business School of Innovation Management Tokyo Japan Universitas Negeri Malang Department of Biology Malang Indonesia Universitas Brawijaya Department of Business Administration Malang Indonesia

ISBN: (纸本)9781665485845

this study aims to design an idea lab or village idea lab as a digital platform An idea lab is defined as an infrastructure developed for gathering in, creating ideas, and brainstorming. the idea lab program adopts the concept of opportunities of learning which focuses on how in learning rather than what. Each group of participants must be able to carry out some activities, namely: defining problems, obtaining data and information, filtering data, expanding initial ideas, and finally applying these ideas (creativity and brainstorming techniques). this study used the User-Centered Design (UCD) method consisting of four stages, namely, (1) understand the context of use, (2) specify user requirements, (3) design solutions, and (4) evaluate. Before developing the platform, the researchers explore the concept of idea lab from empirical and theoretical perspectives. User experience evaluation using the User Experience Questionnaire (UEQ) and usability testing using the System Usability Scale (SUS). the SUS resulted in a final score of 64, which means in the acceptable category. EOQ test concluded that the user experience of the developed product is quite good. © 2022 IEEE.

关键词： Java programming language

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Automating Reasoning with Standpoint logic via Nested Sequents 19

Automating Reasoning with Standpoint Logic via Nested Sequen...

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19th international conference on Principles of Knowledge Representation and Reasoning, KR 2022

作者： Lyon, Tim S. Álvarez, Lucía Gómez Computational Logic Group Faculty of Computer Science TU Dresden Germany

ISBN: (纸本)9781956792010

Standpoint logic is a recently proposed formalism in the context of knowledge integration, which advocates a multiperspective approach permitting reasoning with a selection of diverse and possibly conflicting standpoints rather than forcing their unification. In this paper, we introduce nested sequent calculi for propositional standpoint logics-proof systems that manipulate trees whose nodes are multisets of formulae-and show how to automate standpoint reasoning by means of non-deterministic proof-search algorithms. To obtain worst-case complexity-optimal proof-search, we introduce a novel technique in the context of nested sequents, referred to as coloring, which consists of taking a formula as input, guessing a certain coloring of its subformulae, and then running proof-search in a nested sequent calculus on the colored input. Our technique lets us decide the validity of standpoint formulae in CoNP since proof-search only produces a partial proof relative to each permitted coloring of the input. We show how all partial proofs can be fused together to construct a complete proof when the input is valid, and how certain partial proofs can be transformed into a counter-model when the input is invalid. these "certificates" (i.e. proofs and counter-models) serve as explanations of the (in)validity of the input. © 19th international conference on Principles of Knowledge Representation and Reasoning, KR 2022. All rights reserved.

关键词： Calculations

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TriggerZoo: A Dataset of Android Applications Automatically Infected with logic Bombs

TriggerZoo: A Dataset of Android Applications Automatically ...

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19th international conference on Mining Software Repositories (MSR)

作者： Samhi, Jordan Bissyande, Tegawende F. Klein, Jacques Univ Luxembourg SnT Luxembourg Luxembourg

ISBN: (纸本)9781450393034

Many Android apps analyzers rely, among other techniques, on dynamic analysis to monitor their runtime behavior and detect potential security threats. However, malicious developers use subtle, though efficient, techniques to bypass dynamic analyzers. logic bombs are examples of popular techniques where the malicious code is triggered only under specific circumstances, challenging comprehensive dynamic analyses. the research community has proposed various approaches and tools to detect logic bombs. Unfortunately, rigorous assessment and fair comparison of state-of-the-art techniques are impossible due to the lack of ground truth. In this paper, we present TRIGGERZOO, a new dataset of 406 Android apps containing logic bombs and benign trigger-based behavior that we release only to the research community using authenticated API. these apps are real-world apps from Google Play that have been automatically infected by our tool ANDROBOMB. the injected pieces of code implementing the logic bombs cover a large pallet of realistic logic bomb types that we have manually characterized from a set of real logic bombs. Researchers can exploit this dataset as ground truth to assess their approaches and provide comparisons against other tools.

关键词： Data privacy Runtime Codes Weapons Malware Behavioral sciences Internet

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