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28th International Conference on Knowledge Based and intelligent information and Engineering systems, KES 2024

作者： Paradowski, Bartosz Gajewski, Mariusz Wilczynski, Andrzej Salabun, Wojciech National Institute of Telecommunications National Research Institute ul. Szachowa 1 Warsaw04-894 Poland Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland Department of Computer Science Faculty of Computer Science and Telecommunications Cracow University of Technology Warszawska 24 Krakow31-155 Poland

As civilization advances, decision-making problems become increasingly complex, posing significant challenges in deriving optimal solutions. The field of multi-criteria decision analysis (MCDA) has evolved to address these complexities;however, single-solution approaches are often inadequate in multi-decision-maker scenarios, necessitating group decision-making methods. This study proposes an alternative compromise solution for evaluating electric car performance, examining various compromise approaches, including voting methods like Borda and Copeland counts, and more advanced techniques such as Iterative Compromise Ranking Analysis (ICRA), Improved Borda, HQ compromise, Dominance-directed graph, and Rank position methods. These methods were assessed using two ranking correlation coefficients to evaluate their effectiveness in multi-decision-maker scenarios. Results indicate that while minor differences in rankings were observed based on the chosen compromise method, these differences could influence decision-making outcomes. The analysis highlights the importance of selecting methods that align with specific needs and expectations. Future research should focus on simulation-based studies to better understand the characteristics of each method and apply these methods to real-world case studies to determine their suitability in various contexts. © 2024 The Authors.

关键词： Optimal systems

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Towards Designing a Medication Assistive intelligent System with Automated Insulin-dose Prediction for Elderlies

Towards Designing a Medication Assistive Intelligent System ...

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International Conference on Electrical, computer and Communication Engineering (ECCE)

作者： Abrar Ahmed Minhazul Islam Mahi M. Akhtaruzzaman Jamal Uddin Tanvin Fahim Shahryer Sachitra Halder Muhammad Towfiqur Rahman Md Shofiqul Islam Department of Computer Science and Engineering Military Institute of Science and Technology Dhaka Bangladesh Quantum Robotics and Automation Research Group (QRARG) Dhaka Bangladesh Department of Computer Science & Engineering University Asia Pacific (UAP) Dhaka Bangladesh Institute for Intelligent Systems Research and Innovation (IISRI) Deakin University Geelong Victoria

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Medication management poses significant challenges for many patients, particularly the elderlies, who often struggle with keeping track of their medication schedules and taking the correct dosages. To address this issue, this study aims to design an AI-integrated Medication Management and Assistive Unit (AMMAU) for elderlies with some important features like, schedule reminder, medicine recognition and count, early indication of shortage, sorted slots, and so on. Automated insulin-dose prediction and alert system makes the system unique and more demanding at these current scenarios. For this study, a suitable machine learning model is designed, analyzed, verified, and embedded in the proposed system so that the elderly diabetic patients can get alert, further compare with the current insulin-doses. Though, the proposed system is currently focusing on only the Basal insulin doses prediction, the system will definitely reduce the risks associated with wrong management of medication by degrading the chances of missed doses or taking wrong pills for elderlies at home.

关键词： Training Schedules Analytical models Prototypes Machine learning Predictive models Internet of Things Older adults Insulin Physical design

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Shape Sensing Stretchable Sensor Grid Towards Camera-Less Motion Capture

Shape Sensing Stretchable Sensor Grid Towards Camera-Less Mo...

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IEEE SENSORS

作者： Joseph Karam Aiden Shaevitz Joseph R. Davidson Matthew L. Johnston School of Electrical Engineering and Computer Science Oregon State University Corvallis OR USA Collaborative Robotics and Intelligent Systems Institute Oregon State University Corvallis OR USA

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

Stretchable electronics and conformal sensors are valuable for applications in soft robotics and wearable devices. Here, we demonstrate a stretchable sensor sheet with integrated readout for measuring strain and orientation across the sheet. Conductive liquid metal wires encased in silicone measure multi-axis strain. These strain sensors, paired with precision 9-axis IMUs mounted on PCBs embedded in the silicone, enable a shape-sensing, stretchable sensor grid. A prototype is presented first with a single strain sensor and IMU pair, which is charac-terized and calibrated for higher accuracy. Then, a larger scale stretchable grid with 24 strain sensors and 16 IMUs is presented. A four-wire liquid metal bus delivers power to the system and serves as a data communication bus. Long-term, our approach may enable motion capture and shape reconstruction without the need for external cameras or instrumented environments.

关键词： Liquids Shape Metals Soft robotics Strain measurement Capacitive sensors Motion capture Wearable devices Wearable sensors Strain

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The Sample Complexity of Online Reinforcement Learning: A Multi-model Perspective

arXiv

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arXiv 2025年

作者： Muehlebach, Michael He, Zhiyu Jordan, Michael I. Max Planck Institute for Intelligent Systems Tuebingen Germany Department of Computer Science University of California Berkeley United States

We study the sample complexity of online reinforcement learning for nonlinear dynamical systems with continuous state and action spaces. Our analysis accommodates a large class of dynamical systems ranging from a finite set of nonlinear candidate models to models with bounded and Lipschitz continuous dynamics, to systems that are parametrized by a compact and real-valued set of parameters. In the most general setting, our algorithm achieves a policy regret of O(Nǫ2+ln(m(ǫ))/ǫ2), where N is the time horizon, ǫ is a user-specified discretization width, and m(ǫ) measures the complexity of the function class under consideration via its packing number. In the special case where the dynamics are parametrized by a compact and real-valued set of parameters (such as neural networks, transformers, etc.), we prove a policy regret of O(√Np), where p denotes the number of parameters, recovering earlier sample-complexity results that were derived for linear time-invariant dynamical systems. While this article focuses on characterizing sample complexity, the proposed algorithms are likely to be useful in practice, due to their simplicity, the ability to incorporate prior knowledge, and their benign transient behavior. © 2025, CC BY.

关键词： Reinforcement learning

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Advanced Security Approach for Building Secure Containerized Manufacturing Digital Twins

Advanced Security Approach for Building Secure Containerized...

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2024 IET International Conference on Engineering Technologies and Applications, ICETA 2024

作者： Lin, Yu-Chuan Chiu, Po-Kai Suryajaya, Benny Department of Computer Science and Information Engineering Chinese Culture University Taipei Taiwan Institute of Manufacturing Information and Systems National Cheng Kung University Tainan Taiwan Intelligent Manufacturing Research Center National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9781837242672

In the era of digital transformation, containerized systems and digital twins are vital technologies in intelligent manufacturing. Our previous research, the Implementation Framework of Digital Twins for intelligent Manufacturing (IF-DTiM), lacks comprehensive security features[1]. To address this critical gap, we propose the Advanced Security Approach for Building Secure Containerized Manufacturing Digital Twins (ASABS-CMDT), integrating automated tools for detecting vulnerabilities, container image creation, and secure digital signing, all within DevSecOps practices. Case studies show that ASABS-CMDT significantly enhances system security and reduces development time, offering valuable insights for practitioners in intelligent manufacturing. © The Institution of Engineering & Technology 2024.

关键词： Smart manufacturing

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High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System

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Journal of Bionic Engineering 2022年第2期19卷 299-313页

作者： Yinlong Zhang Wei Liang Sichao Zhang Xudong Yuan Xiaofang Xia Jindong Tan Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China The School of Computer Science and Technology Xidian UniversityXi’an 710071China Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeKonxville 37996USA Department of Automation Technology ABB Corporate Research Sweden72178 VästerasSweden

Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured *** robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical *** paper introduces a novel calibration ***,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint ***,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent *** calibration has been evaluated on our collected visual inertial-manipulator *** systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method.

关键词： Bio-inspired robotic system Monocular camera IMU Manipulator Calibration

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Early Prediction of Cryptocurrency Price Decline: A Deep Learning Approach 26

Early Prediction of Cryptocurrency Price Decline: A Deep Lea...

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26th International Conference on computer and Information Technology, ICCIT 2023

作者： Akter, Mst Shapna Shahriar, Hossain Rahman, Md Abdur Rahman, Muhammad Cuzzocrea, Alfredo University of West Florida Department of Intelligent Systems and Robotics United States University of West Florida Center for Cybersecurity United States Jahangirnagar University Department of Mathematics Dhaka Savar Bangladesh Clayton State University Department of Computer Science United States University of Calabria IDEA Lab Rende Italy

ISBN: (纸本)9798350359015

In recent times, the cryptocurrency market has emerged as one of the fastest-growing financial markets worldwide. It is, however, known for its high volatility and illiquidity compared to traditional markets such as equities, foreign exchange, and commodities. This inherent risk creates uncertainty among investors. The aim of this research is to forecast the level of risk in the cryptocurrency market. To assist cryptocurrency investors in navigating these challenges, we propose an approach that involves calculating the risk factor based on existing parameters. We employed various machine learning algorithms, including CNN, LSTM, BiLSTM, and GRU, to predict the risk factor in twenty elements of the cryptocurrency market. Through extensive experimentation, we developed a new model that outperformed existing models, achieving the highest Root Mean Square Error (RMSE) value of 1.3229 and the lowest RMSE value of 0.0089. Furthermore, we tested the generalization ability of our proposed model on a new dataset, different from the one used for training. Even with this new dataset, our model displayed robust performance. In contrast, the other existing models achieved higher RMSE values, with the highest being 14.5092 and the lowest 0.02769. By adopting our approach, investors can trade more confidently in complex and challenging financial assets such as Bitcoin, Ethereum, and Dogecoin. Our proposed model demonstrates superior performance and generalization capabilities, providing valuable insights for participants in the cryptocurrency market. © 2023 IEEE.

关键词： Cryptocurrency deep learning ensemble learning time-series forecasting volatility

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Design of Capsule Robot for Magnetic Gastric Biopsy and Drug Administration 20

Design of Capsule Robot for Magnetic Gastric Biopsy and Drug...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Xu, Zhihui Li, Zongze Liu, Shoubin Hu, Chengzhi Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen China Guangdong Prov. Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China Harbin Institute of Technology School of Mechanical and Electrical Engineering Shenzhen China

ISBN: (纸本)9798350320831

Capsule robots have emerged as a promising tool for the early diagnosis of gastrointestinal diseases. Unlike conventional gastroscopy, they offer the potential for minimally invasive or even non-invasive treatment, and can alleviate discomfort and pain in patients. However, current capsule robots have some limitations. For instance, they lack stomach tissue biopsy and drug administration functions, and the capsule robot used for biopsy does not consider the tolerance of gastrointestinal tissue. Similarly, the capsule robot used for drug administration does not account for the outlet speed of drug administration. This paper proposes a new biopsy method using a magnetically manipulated capsule robot and analyzes the principles governing the robot's manipulation during the biopsy and drug administration processes. Furthermore, an ANSYS gastric model was established and used to simulate and experimentally analyze damage to the gastric tissue model from different types of biopsy needles and their moving speeds. The appropriate type of biopsy needle and moving speed were determined to prevent damage to the gastric tissue. The study also used FLUENT to determine the appropriate thrust at the entrance of the drug cavity and the impact of the drug density on the drug outlet velocity to ensure complete adherence of the drug to the lesion. © 2023 IEEE.

关键词： Biopsy

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Magnetically Driven Capsule Robot for Multi-Targeted Biopsy and Drug Delivery in Stomach

Magnetically Driven Capsule Robot for Multi-Targeted Biopsy ...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Xu, Zhihui Wei, Tanyong Li, Zongze Huang, Ding Liu, Shoubin Hu, Chengzhi Southern University of Science and Technology Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Shenzhen China Southern University of Science and Technology Guangdong Prov. Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen China Harbin Institute of Technology School of Mechanical Engineering and Automation Shenzhen China

ISBN: (纸本)9798350325706

Capsule robots have emerged as a promising solution for non-invasive and painless screening of gastrointestinal diseases, offering significant advantages in patient comfort and reduced risk of cross-infection. Despite these advantages, existing capsule robots fall short in their ability to conduct targeted biopsies and deliver drugs to specific gastric lesions. To address this limitation, this paper presents the design and development of a magnetically driven capsule robot that leverages visual feedback to achieve accurate targeting for biopsy and drug administration in gastric lesions. Internal magnets, responsive to an external gradient magnetic field, enable the controlled propulsion of the capsule robot. A kinetic model of the capsule robot is analyzed, allowing it to recognize lesion contours through the endoscopic camera. This recognition determines the rotation angle or small adjustments required for the capsule robot's attitude and positioning. Experimental results in a simplified in vitro stomach model showcase the capability of the capsule robot to achieve targeted biopsy and drug delivery. These results highlight the potential feasibility of the proposed capsule robot in enhancing diagnostic accuracy and treatment efficacy with broader applications within the realm of gastric healthcare. © 2023 IEEE.

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NeRF and Gaussian Splatting SLAM in the Wild

arXiv

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arXiv 2024年

作者： Schmidt, Fabian Enzweiler, Markus Valada, Abhinav Institute for Intelligent Systems Esslingen University of Applied Sciences Germany Department of Computer Science University of Freiburg Germany

Navigating outdoor environments with visual Simultaneous Localization and Mapping (SLAM) systems poses significant challenges due to dynamic scenes, lighting variations, and seasonal changes, requiring robust solutions. While traditional SLAM methods struggle with adaptability, deep learning-based approaches and emerging neural radiance fields as well as Gaussian Splatting-based SLAM methods, offer promising alternatives. However, these methods have primarily been evaluated in controlled indoor environments with stable conditions, leaving a gap in understanding their performance in unstructured and variable outdoor settings. This study addresses this gap by evaluating these methods in natural outdoor environments, focusing on camera tracking accuracy, robustness to environmental factors, and computational efficiency, highlighting distinct trade-offs. Extensive evaluations demonstrate that neural SLAM methods achieve superior robustness, particularly under challenging conditions such as low light, but at a high computational cost. At the same time, traditional methods perform the best across seasons but are highly sensitive to variations in lighting conditions. The code of the benchmark is publicly available at https://***/iis-esslingen/nerf-3dgs-benchmark. Copyright © 2024, The Authors. All rights reserved.

关键词： Lighting

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