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The Concept and Means of Adaptive Shading 12

The Concept and Means of Adaptive Shading

引用

12th international conference on Advanced Computer Information Technologies, ACIT 2022

作者： Romanyuk, Olexandr Romanyuk, Oksana Chekhmestruk, Roman Mykhaylov, Pavlo Maidaniuk, Volodymyr Korobeinikova, Tetiana Vinnytsia National Technical University Faculty of Information Technologies and Computer Engineering Vinnytsia Ukraine 3D Generation Ua Vinnitsa Ukraine Ceo 3D Gneration GmbH Dortmund Germany Institute of Computer Technologies Automation and Metrology Lviv Polytechnic National University Lviv Ukraine

ISBN: (数字)9781665410502

ISBN: (纸本)9781665466479

In computer graphics systems during the formation of realistic images in most cases are used models of shading, which take into account the background, diffuse and specular components of color, which may be redundant and affect the time of formation of three-dimensional images. This is due to the fact that specular highlights on the surface of the object is on average about 10% of its total area, and therefore the use of computationally complex models for the whole object is impractical, as the use of simple and complex lighting models gives identical results for specular highlight zones. The concept of structural-adaptive shading is developed, which consists in preliminary analysis of the triangulation structure of a three-dimensional object with subsequent adaptive choice of lighting models and shading methods, and provides increased productivity of shading by removing redundant calculations that do not affect the quality. © 2022 IEEE.

关键词： Rendering (computer graphics)

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CDHD: Contrastive Dreamer for Hint Distillation 48

CDHD: Contrastive Dreamer for Hint Distillation

引用

48th IEEE international conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Yu, Le Hua, Tongyan Yang, Wenming Ye, Peng Liao, Qingmin Tsinghua University Shenzhen International Graduate School China Country Garden Group Bright Dream Robotics China

ISBN: (纸本)9781728163277

Replaying previous training data is the most effective approach for Class-Incremental Learning (CIL), with its performance bounded by data availability. Therefore, many recent studies consider the Data-Free Class-Incremental Learning (DFCIL) problem that requires no previous data. However, the existing methods do not consider synthesising data of heterogeneity, thus limiting models' generalizability. Such homogenous images further hinder the knowledge distillation process when regularising only the deeper layers close to the output, resulting in catastrophic forgetting. To address these issues, we present CDHD: a contrastive dreamer for hint distillation. Our approach starts with training a generator for data synthesis. A model inversion technique is introduced to obtain a generator capable of producing heterogeneous images from the classifier by imposing the ContRastive Loss. Moreover, to better transfer the previous knowledge to the current model, we force the teacher network to provide more general knowledge to its students by enforcing the Hint Loss in shallower layers rather than only in deeper ones. We validate the performance of CDHD on CIFAR-100 for various tasks and compare it against the SOTA baseline for DFCIL, demonstrating our superiorities and thus constituting a new benchmark. © 2023 IEEE.

关键词： Distillation

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A fast simulation method for magnetically driven deformation of a sheet micro soft robot 8

A fast simulation method for magnetically driven deformation...

引用

2022 8th international conference on Mechanical Engineering, Materials and automation Technology, MMEAT 2022

作者： Gao, Jian Rong, Weibin Gao, Peng Li, Dongjie Wang, Lefeng State Key Laboratory of Robotics and System Harbin Institute of Technology Heilongjiang Harbin150001 China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology Heilongjiang Harbin150080 China

The magnetically driven micro soft robot is a hot research topic in the field of micro robotics. The magnetic torque of each part of the robot rotates with its deformation, so the magnetic torque and magnetic force to which the robot is subjected are difficult to be calculated directly. The lack of physical interfaces for torque distribution in many finite element software reduces the speed and accuracy of calculating the deformation of a robot using finite element simulation methods. In this paper, a fast simulation method to convert the local magnetic torque into equivalent load density for the deformation mode of the sheet micro soft robot is proposed. A finite element model of the fabricated micro soft robot is established, and the deformation and total magnetic moment of the robot under different magnetic field strength and magnetic field gradient are simulated and calculated. Experiments are executed to verify the validity of the simulation results. © Published under licence by IOP Publishing Ltd.

关键词： Robots

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Searching & Generating Discrete-Event Systems 18

Searching & Generating Discrete-Event Systems

引用

18th international conference on Informatics in Control, automation and robotics (ICINCO)

作者： Helliwell, T. J. Morgan, B. Mahfouf, M. Univ Sheffield Automat Control & Syst Engn Dept Sheffield S Yorkshire England Univ Shefeld Adv Mfg Res Ctr AVIRC Sheffield S Yorkshire England

ISBN: (纸本)9789897585227

In this paper we introduce a new method for the automatic generation and computer experimentation of Discrete-Event Systems (DES). We introduce the concept that DES descriptions may be used to define a searchable configuration space. Configuration instances in this space a represented as a permutation encoding which shows the number-of and types-of resources in a given configuration. Each instance is checked that the number of resources does not exceed a maximum and whether a fixed set of processes (a decomposed goal of uncertain time intervals drawn from a Gaussian distribution) can be logically completed on the given set of resources. If the permutation instance satisfies these constraints, it is subsequently constructed as a simulation model to quantify completion through global features of makespan and total processing time. We claim this is the basis for a powerful tool in high-level informed design of these types of systems that have hitherto avoided autonomous description or have been previously individually designed using time consuming manually defined programs.

关键词： Generative models Discrete-Event Systems Variable Structures Event Calculus Metaprogramming

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AlphaSOC: Reinforcement Learning-based Cybersecurity automation for Cyber-Physical Systems 13

AlphaSOC: Reinforcement Learning-based Cybersecurity Automat...

引用

13th ACM/IEEE international conference on Cyber-Physical Systems (ICCPS )

作者： Silva, Ryan Hickert, Cameron Sarfaraz, Nicolas Brush, Jeff Silbermann, Josh Sookoor, Tamim Johns Hopkins Univ Appl Phys Lab Baltimore MD 21218 USA

ISBN: (纸本)9781665409674

Achieving agile and resilient autonomous capabilities for cyber defense requires moving past indicators and situational awareness into automated response and recovery capabilities. The objective of the AlphaSOC project is to use state of the art sequential decision-making methods to automatically investigate and mitigate attacks on cyber physical systems (CPS). To demonstrate this, we developed a simulation environment that models the distributed navigation control system and physics of a large ship with two rudders and thrusters for propulsion. Defending this control network requires processing large volumes of cyber and physical signals to coordinate defensive actions over many devices with minimal disruption to nominal operation. We are developing a Reinforcement Learning (RL)-based approach to solve the resulting sequential decision-making problem that has large observation and action spaces.

关键词： Reinforcement Learning Cybersecurity Cyber-Physical System

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HILO: A Large-Scale Heterogeneous Object Dataset for Benchmarking Robotic Grasping Approaches

HILO: A Large-Scale Heterogeneous Object Dataset for Benchma...

引用

international conference on Autonomous Robots and Agents, ICARA

作者： Xinchao Song Sean Banerjee Natasha Kholgade Banerjee Dept. of Computer Science Clarkson University Potsdam NY USA Dept. of Computer Science & Engineering Wright State University Dayton OH USA

ISBN: (数字)9798331509231

ISBN: (纸本)9798331509248

Robust object manipulation is essential for robotics applications in real-world environments, especially when handling diverse and complex everyday objects. To facilitate this research, we present HILO, a large-scale dataset of 253 real-world everyday objects and 288 diverse scenes. HILO bridges a crucial gap in existing manipulation datasets through its heterogeneity and dual-resolution approach, combining high-resolution individual object scans with low-resolution scans of cluttered scenes. This provides both the precise geometric data needed for grasp planning and realistic environmental context. The dataset's comprehensive representations enable rigorous benchmarking of robotic grasping algorithms. Our evaluation of three leading grasping algorithms-Contact-GraspNet, GraspNet Baseline, and DexNet 4.0-reveals critical trade-offs between grasp quantity and quality, demonstrating the dataset's value in advancing robotic grasping research. HILO's rich object diversity and dual-resolution methodology provide a foundation for developing more versatile robotic systems capable of reliable real-world robotic manipulation. Our dataset is available at https://***/hilo_dataset/.

关键词： Bridges automation Diversity reception Collaboration Grasping Benchmark testing Diversity methods Planning Reliability Robots

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Intelligent automation in Stock Market Prediction: A Survey of Automated models 4

Intelligent Automation in Stock Market Prediction: A Survey ...

引用

4th IEEE international conference on Smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2023

作者： Anirudhan Adukkathayar, C. Hulipalled, Vishwanath R. Simha, Jay Bharthish Chundi, Ramesh Reva University Bangalore India Reva University School Of Computing And Information Technology Bangalore India Reva University Abiba Systems Cto And Race Labs Bangalore India Reva University School Of Computer Science And Applications Bangalore India

ISBN: (纸本)9798350384628

In an era marked by global digitization, the landscape of stock market prediction has undergone a transformative shift, ushering in a new era of technologically-driven trading. With soaring market capitalization, stock trading has emerged as a focal point for financial investment. Analysts and researchers have pioneered tools and methodologies to anticipate stock price movements, empowering investors in making informed decisions. Advanced trading models now harness unconventional textual data from social platforms, leveraging cutting-edge machine learning techniques like text data analytics and ensemble methods to significantly enhance prediction accuracies. Despite these advancements, the dynamic, erratic, and often chaotic nature of stock market data continues to present formidable challenges. This study elucidates the systematic application of machine learning-based approaches and sentimental analysis approaches for stock market prediction, grounded in a versatile framework. A critical analysis of findings from the reputable digital libraries and databases including ACM digital library and Scopus, forms the cornerstone of this inquiry. Moreover, an expansive comparative analysis was conducted to delineate key trends and significant directions. This comprehensive exploration aims to furnish budding researchers with a foundational understanding of this burgeoning domain and pave the way for further inquiry into promising avenues. © 2023 IEEE.

关键词： Sentiment analysis

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Adaptive Admittance Control with Dynamical Systems for Optimized Motion Adaptation

Adaptive Admittance Control with Dynamical Systems for Optim...

引用

international conference on Advanced robotics and Mechatronics (ICARM)

作者： Yuting Guo Guangzhu Peng Chenguang Yang School of Automation Nanjing University of Information Science and Technology Nanjing China Department of Computer Science University of Liverpool Liverpool UK

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Trajectory adaptation is a crucial ability for robots to perform interactive tasks with the environment. This paper develops a motion adaptation framework for robots that learns and adapts the task trajectory in unknown environments. Firstly, we utilize dynamical system (DS) to learn the task trajectory of robots online through demonstration. When the robot is performing interactive tasks with the environment, a force observer based admittance control method is designed so that the robot can adaptively optimize and adjust reference trajectory. Moreover, we design a robot position controller based on neural learning to provide a precise trajectory tracking performance. Finally, the global stability of the system is analyzed by the Lyapunov theory, and a set of simulations are conducted to evaluate the motion adaptability of the proposed framework.

关键词： Adaptation models Trajectory tracking Heuristic algorithms Force Aerospace electronics Stability analysis Trajectory Dynamical systems Robots Admittance control

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Time-Aware Multiway Adaptive Fusion Network for Temporal Knowledge Graph Question Answering 48

Time-Aware Multiway Adaptive Fusion Network for Temporal Kno...

引用

48th IEEE international conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Liu, Yonghao Liang, Di Fang, Fang Wang, Sirui Wu, Wei Jiang, Rui Centre for Natural Language Processing Meituan Inc Beijing China Tsinghua University Department of Automation Beijing China

ISBN: (纸本)9781728163277

Knowledge graphs (KGs) have received increasing attention due to its wide applications on natural language processing. However, its use case on temporal question answering (QA) has not been well-explored. Most of existing methods are developed based on pre-trained language models, which might not be capable to learn temporal-specific presentations of entities in terms of temporal KGQA task. To alleviate this problem, we propose a novel Time-aware Multiway Adaptive (TMA) fusion network. Inspired by the step-by-step reasoning behavior of humans. For each given question, TMA first extracts the relevant concepts from the KG, and then feeds them into a multiway adaptive module to produce a temporal-specific representation of the question. This representation can be incorporated with the pre-trained KG embedding to generate the final prediction. Empirical results verify that the proposed model achieves better performance than the state-of-the-art models in the benchmark dataset. Notably, the Hits@1 and Hits@10 results of TMA on the CronQuestions dataset's complex questions are absolutely improved by 24% and 10% compared to the best-performing baseline. Furthermore, we also show that TMA employing an adaptive fusion mechanism can provide interpretability by analyzing the proportion of information in question representations. © 2023 IEEE.

关键词： knowledge graph question answering neural language processing Temporal knowledge graph question answering

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Developing an Agent-Based Simulation Model for Predicting Technology Acceptance at Border Crossing Points

Developing an Agent-Based Simulation Model for Predicting Te...

引用

international conference on Autonomous Robots and Agents, ICARA

作者： Sarang Shaikh Sule Yildirim Yayilgan Dept. of Information Security and Communication Technology Norwegian University of Science and Technology (NTNU) Gjovik Norway

In this paper, we are focusing on the use of agent-based approach to generate simulations of various scenarios for border crossing points and making technology acceptance predictions. This paper is related to the Horizon 2020 project METICOS 1 1 https://***/, for which we are extracting user (traveler and border control staff) perceptions from sources such as online social networks e.g., Twitter, Web, Interviews, Questionnaires etc. However, for the scope of this paper we have only included the synthetic data for the experiments to validate the proposed simulation model. The existing studies made a strong justification for choosing this approach to model the defined problem. To the best of our knowledge, this paper is a first research study focusing on defining how agent-based modeling and simulation can be used to model border crossing scenarios and predicting the acceptance of the border control technologies by explaining travelers' profile based on synthetic data, perceptions based on manual rules. This is important for stakeholders who take decisions related to what technologies to place at the border crossing points and what features such technologies should have to improve throughputs and traveler and border staff satisfaction.

关键词： Social networking (online) Focusing Manuals Predictive models Agent-based modeling Throughput Data models

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