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检索条件"任意字段=22nd International Conference on Logic Programming"

共 2139 条记录，以下是401-410 订阅

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Resource Allocation in Underlay Network with User Diversity

Resource Allocation in Underlay Network with User Diversity

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international conference on Communication Technology (ICCT)

作者： Jinting Liu Chiya Zhang Chunlong He School of Electronic and Information Engineering Harbin Institute of Technology Shenzhen Shenzhen China National Mobile Communications Research Laboratory Southeast University Nanjing China

Device-to-Device (D2D) communication can enhance the spectrum utilization rate by multiplexing downlink resources in a 5G cellular network. However, it also introduces interference. We formulate an optimization problem with the objective of optimizing the transmission total rate of the celluar users (CUs) and D2D pairs while meeting the minimum necessary rate of cellular users and D2D pairs. We approach this issue by optimizing the transmitted beamforming, and power allocation jointly. The problem is decoupled into two subproblems. To achieve the optimization objective, a RPSO (Revised Particle Swarm Optimization Algorithm) in section beamforming optimization is formulated, and in the power allocation step the companion matrix is utilized to determine the optimal power allocation. The simulation demonstrates that the suggested approach successfully increased both the sum rate and connection rate while maintaining quality of service (QoS).

关键词： Multiplexing Array signal processing Simulation Quality of service programming Device-to-device communication Resource management

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GitHub Considered Harmful? Analyzing Open-Source Projects for the Automatic Generation of Cryptographic API Call Sequences

GitHub Considered Harmful? Analyzing Open-Source Projects fo...

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IEEE international conference on Software Quality, Reliability and Security (QRS)

作者： Catherine Tony Nicolás E. Díaz Ferreyra Riccardo Scandariato Institute of Software Security Hamburg University of Technology Hamburg Germany

GitHub is a popular data repository for code examples. It is being continuously used to train several AI-based tools to automatically generate code. However, the effectiveness of such tools in correctly demonstrating the usage of cryptographic APIs has not been thoroughly assessed. In this paper, we investigate the extent and severity of misuses, specifically caused by incorrect cryptographic API call sequences in GitHub. We also analyze the suitability of GitHub data to train a learning-based model to generate correct cryptographic API call sequences. For this, we manually extracted and analyzed the call sequences from GitHub. Using this data, we augmented an existing learning-based model called DeepAPI to create two security-specific models that generate cryptographic API call sequences for a given natural language (NL) description. Our results indicate that it is imperative to not neglect the misuses in API call sequences while using data sources like GitHub, to train models that generate code.

关键词： Training Computer languages Codes Natural languages Software quality programming Data models

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Model-free PAC Time-Optimal Control Synthesis with Reinforcement Learning

Model-free PAC Time-Optimal Control Synthesis with Reinforce...

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ACM and IEEE international conference on Formal Methods and Models for Co-Design (MEMOCODE)

作者： Mengyu Liu Pengyuan Lu Xin Chen Oleg Sokolsky Insup Lee Fanxin Kong Department of Computer Science and Engineering University of Notre Dame Notre Dame IN Department of Computer and Information Science University of Pennsylvania Philadelphia PA Department of Computer Science University of New Mexico Albuquerque NM

ISBN: (数字)9798350378023

ISBN: (纸本)9798350378030

Reaching a target safely and quickly is a control goal pursued by various applications, such as post-disaster rescue robots and industrial shipment. However, it is hard to formally guarantee safety and time-optimality under unknown dynamics via model-free controller synthesis algorithms. As a response, we propose a model-free reinforcement learning (RL) algorithm that synthesize a controller to reach a predefined target set of states with a probabilistic guarantee of time optimality, i.e., the actual reaching time is bounded close to the shortest time possible with high probability, and the bound becomes tighter when more training data is sampled. Our algorithm leverages a reward function that based on signal temporal logic (STL) robustness to reward fast reaching. With this reward function, we prove that Probably Approximately Correct (PAC) optimality in the state-value function implies PAC optimality in reach time. Then, we build our algorithm by extending Deplayed Gaussian Process Q learning (DGPQ) algorithm with a safety margin to protect the controlled agent. Consequently, our algorithm guarantees safety and a PAC bound in recovery time. Experiments show our method can achieve $\mathbf{9 7. 7 \%}$ success rate to reach the target with in the maximum time tolerance and outperform baselines.

关键词： Heuristic algorithms Training data Approximation algorithms Probabilistic logic Picture archiving and communication systems Robustness Stability analysis Safety System analysis and design Rescue robots

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22nd international conference on Enterprise Information Systems, ICEIS 2020

22nd International Conference on Enterprise Information Syst...

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22nd international conference on Enterprise Information Systems, ICEIS 2020

ISBN: (纸本)9783030754174

The proceedings contain 41 papers. The special focus in this conference is on Enterprise Information Systems. The topics include: Fast and Efficient Parallel Execution of SARIMA Prediction Model;an Approach to Intelligent Control Public Transportation System Using a Multi-agent System;comparative Evaluation of the Supervised Machine Learning Classification Methods and the Concept Drift Detection Methods in the Financial Business Problems;sammon Mapping-Based Gradient Boosted Trees for Tax Crime Prediction in the City of São Paulo;extraction of Speech Features and Alignment to Detect Early Dyslexia Evidences;an Extended Secondary Study to Characterize the Influence of Developers Sentiments on Practices and Artifacts in Open Source Software Projects;improving Quality of Use-Case Models by Correlating Defects, Difficulties, and Modeling Strategies;iVolunteer - A Platform for Digitization and Exploitation of Lifelong Volunteer Engagement;an Investigation of Currently Used Aspects in Model Transformation Development;streaming Set Similarity Joins;Software Evolution and Maintenance Using an Agile and MDD Hybrid Processes;DSL Based Approach for Building Model-Driven Questionnaires;modeling of Robot Interaction in Coalition Through Smart Space and Blockchain: Precision Agriculture Scenario;a Capability Based Method for Development of Resilient Digital Services;adopting Agile Software Development Combined with User-Centered Design and Lean Startup: A Systematic Literature Review on Maturity Models;Evaluating a LSTM Neural Network and a Word2vec Model in the Classification of Self-admitted Technical Debts and Their Types in Code Comments;from Simple to Structural Clones: Tapping the Benefits of Non-redundancy;SACIP: An Agent-Based Constructionist Adaptive System for programming Beginners;security Architecture Framework for Enterprises.

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A Comparative Study of Hough Transform and PCA for Bolt Orientation Detection

A Comparative Study of Hough Transform and PCA for Bolt Orie...

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IEEE international conference on Industrial Informatics (IndIN)

作者： Antonio Gambale Sonya Coleman Dermot Kerr Philip Vance Emmett Kerr Cornelia Fermuller Yiannis Aloimonos School of Computing Engineering & Intelligent Systems Ulster University Londonderry Northern Ireland Dept. of Electronic & Mechanical Engineering Atlantic Technological University Letterkenny Ireland Institute for Advanced Computer Studies University of Maryland USA

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

In the fields of manufacturing and robotics, accurately determining the orientation of manufacturing components, such as bolts, is a critical yet challenging problem due to the limitations of existing detection methods. This study introduces a novel methodology for addressing this issue, leveraging traditional computer vision techniques, by proposing a streamlined approach that exploits the inherent geometric properties of bolts for orientation detection. Two methods are presented to ascertain the initial axis angle of the bolt: the Progressive Probabilistic Hough Transform (PPHT) and Principal Component Analysis (PCA). These methods are used in conjunction with a novel tip direction detection approach. The results of the study demonstrate consistent accuracy in angle determination, with PPHT and PCA both achieving angular deviations below ±0.5° in the simple dataset, and PCA showing enhanced robustness in the dataset degraded by shadows, with a maximum error under ±1.5°. This research not only reaffirms the viability of fundamental computer vision techniques in modern robotic applications but also sets a precedent for simple, generalisable, and reliable orientation detection solutions. These methods effectively bridge the gap between highly specialised machine learning systems, which often require tailored, complex models and extensive training data, and more universally applicable, straightforward approaches.

关键词： Computer vision Training data Transforms Machine learning Fasteners Probabilistic logic Robustness Manufacturing Informatics Principal component analysis

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SACIP: An Agent-Based Constructionist Adaptive System for programming Beginners 22nd

SACIP: An Agent-Based Constructionist Adaptive System for Pr...

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22nd international conference on Enterprise Information Systems, ICEIS 2020

作者： da S. Esteves, Adson M. Filho, Aluizio Haendchen Raabe, André Dazzi, Rudimar L. S. Rua Uruguay 458 Itajaí Brazil Rua Uruguay 458 Itajaí Brazil

ISBN: (纸本)9783030754174

Brazilian universities have a high dropout rate in Computing courses. We believe E-learning personalized solutions can help to reduce this problem. This paper presents an architectural model for an adaptive system called SACIP that uses learning paths to deliver personalized assistance for students learning to program. Constructivist and constructionist theories were used as guidelines for the system modeling, and a collaborative multiagent system was developed to assist students in their choice of paths. Details of the SACIP implementation on different platforms are described, as well as its benefits and advantages over similar adaptive systems that use learning paths in a distinct manner. The application of SACIP with beginners in programming is aimed to facilitate learning, allow curricular flexibility and help to reduce dropout rates in Computing courses. © 2021, Springer Nature Switzerland AG.

关键词： E-learning

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Differentiating persuasive factors for tourism booking websites: Towards matrix factorization

Differentiating persuasive factors for tourism booking websi...

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international conference on Computational Science and its Applications (ICCSA)

作者： Chien-Sing Lee Yew-Onn Wong Hui-Ying Gui School of Engineering and Technology Sunway University Malaysia

The main challenges to increasing sales, usually lie with persuasion techniques and recommender systems. Persuasion Systems models (PSDs) analyse persuasion context, identifies the key issues and subsequently, enables mapping of persuasion techniques to functional requirements. This paper investigates persuasive factors for tourism booking websites, with the aim of utilizing derived significant factors at different stages, as the bases for weighted criteria analyses, and matrix factorization, integral in fuzzy logic computations. Two parallel case studies are carried out. The first tourism booking website is designed, based on Cialdini's persuasion techniques for the Malaysian hotel/tourism context, and tested with customers and travel agencies. The second study investigates social CRM and associations between gender, age and income on a group of different sample respondents. User evaluation indicates different weighted factors at the search, review and booking stages, as well as different perceptions, with regards to cross-selling. Comparative findings with successful cross-selling companies, such as Lazada and Shoppee further highlight three core influencing factors. These have enabled us to add specificity to some constructs in Oinas-Kukkonen and Harjumaa's PSD dialogue support model, for the sampled Malaysian contexts. This triangulated approach can enable more holistic derivation of requirements and prediction and derivation of initial rules for future decision support systems.

关键词： Fuzzy logic Decision support systems Analytical models Technological innovation Scientific computing Biological system modeling Companies

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Facets of the PIE Environment for Proving, Interpolating and Eliminating on the Basis of First-Order logic 22nd

Facets of the PIE Environment for Proving, Interpolating and...

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22nd international conference on Applications of Declarative programming and Knowledge Management, INAP 2019, the 33rd Workshop on logic programming, WLP 2019, and the 27th Workshop on Functional and Constraint logic programming, WFLP 2019

作者： Wernhard, Christoph Berlin Germany

ISBN: (纸本)9783030467135

PIE is a Prolog-embedded environment for automated reasoning on the basis of first-order logic. Its main focus is on formulas, as constituents of complex formalizations that are structured through formula macros, and as outputs of reasoning tasks such as second-order quantifier elimination and Craig interpolation. It supports a workflow based on documents that intersperse macro definitions, invocations of reasoners, and-formatted natural language text. Starting from various examples, the paper discusses features and application possibilities of PIE along with current limitations and issues for future research. © 2020, Springer Nature Switzerland AG.

关键词： Interpolation

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Complexity of Branch-and-Bound and Cutting Planes in Mixed-Integer Optimization - II 22nd

Complexity of Branch-and-Bound and Cutting Planes in Mixed-I...

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22nd international conference on Integer programming and Combinatorial Optimization (IPCO)

作者： Basu, Amitabh Conforti, Michele Di Summa, Marco Jiang, Hongyi Johns Hopkins Univ Baltimore MD 21218 USA Univ Padua Padua Italy

ISBN: (纸本)9783030738792;9783030738785

We study the complexity of cutting planes and branching schemes from a theoretical point of view. We give some rigorous underpinnings to the empirically observed phenomenon that combining cutting planes and branching into a branch-and-cut framework can be orders of magnitude more efficient than employing these tools on their own. In particular, we give general conditions under which a cutting plane strategy and a branching scheme give a provably exponential advantage in efficiency when combined into branch-and-cut. The efficiency of these algorithms is evaluated using two concrete measures: number of iterations and sparsity of constraints used in the intermediate linear/convex programs. To the best of our knowledge, our results are the first mathematically rigorous demonstration of the superiority of branch-and-cut over pure cutting planes and pure branch-and-bound.

关键词： Integer programming Cutting planes Branching schemes Proof complexity

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Simultaneous Optimization of Task Allocation and Path Planning Using Mixed-Integer programming for Time and Capacity Constrained Multi-Agent Pickup and Delivery

Simultaneous Optimization of Task Allocation and Path Planni...

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international conference on Control, Automation and Systems ( ICCAS)

作者： Takuma Okubo Masaki Takahashi Graduate School of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama Japan Department of System Design Engineering Faculty of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama Japan

Lately, there has been a need to improve the efficiency of material movements within factories and multi-agents are required to perform these tasks. In this study, graphical representation and mixed-integer programming have been adopted for simultaneous optimization of task allocation and path planning for each agent to achieve the following three goals. First, this study realizes time and capacity constrained multi-agent pickup and delivery (TCMAPD) that simultaneously considers time constraints, capacity constraints, and collision avoidance. Previous studies have not considered these constraints simultaneously. Thus, we can solve the problems associated with using multi-agents in actual factories. Second, we achieved TCMAPD that optimizes the collision avoidance between multi-agents. In conventional research, only a single collision avoidance method can be used. However, an appropriate route was selected from a variety of avoidance methods in this study. Hence, we could achieve a more efficient task allocation and path planning with collision avoidance. Third, the proposed method simultaneously optimizes task allocation and path planning for each agent. Previous studies have separately considered the approach of optimizing task allocation and path planning or used the cost of path planning after task allocation to again perform task allocation and path planning. To simultaneously optimize them in a single plan, we have developed a solution-derivable formulation using mixed-integer programming to derive a globally optimal solution. This enables efficient planning with a reduced total time traveled by the agents.

关键词： Costs programming Path planning Production facilities Planning Resource management Time factors

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