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Exploiting autoencoder’s weakness to generate pseudo anomalies

Neural Computing and Applications 2024年第23期36卷 14075-14091页

作者： Astrid, Marcella Zaheer, Muhammad Zaigham Aouada, Djamila Lee, Seung-Ik Department of Artificial Intelligence University of Science and Technology Daejeon34113 Korea Republic of Field Robotics Research Section Electronics and Telecommunications Research Institute Daejeon34129 Korea Republic of Interdisciplinary Centre for Security Reliability and Trust University of Luxembourg Luxembourg1855 Luxembourg Department of Computer Vision Mohamed Bin Zayed University of Artificial Intelligence Abu Dhabi United Arab Emirates

Due to the rare occurrence of anomalous events, a typical approach to anomaly detection is to train an autoencoder (AE) with normal data only so that it learns the patterns or representations of the normal training data. At test time, the trained AE is expected to well reconstruct normal but to poorly reconstruct anomalous data. However, contrary to the expectation, anomalous data are often well reconstructed as well. In order to further separate the reconstruction quality between normal and anomalous data, we propose creating pseudo anomalies from learned adaptive noise by exploiting the aforementioned weakness of AE, i.e., reconstructing anomalies too well. The generated noise is added to the normal data to create pseudo anomalies. Extensive experiments on Ped2, Avenue, ShanghaiTech, CIFAR-10, and KDDCUP datasets demonstrate the effectiveness and generic applicability of our approach in improving the discriminative capability of AEs for anomaly detection. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Anomaly detection

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Real-time Prediction of Fluid Resuscitation Rate for Burn Patients: A Web Based Fuzzy Logic Approach

Real-time Prediction of Fluid Resuscitation Rate for Burn Pa...

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International Conference on computer and Information Technology (ICCIT)

作者： Aminul Islam M. Akhtaruzzaman Department of Computer Science and Engineering Military Institute of Science and Technology (MIST) Dhaka Bangladesh Quantum Robotics and Automation Research Group (QRARG) Dhaka Bangladesh

ISBN: (数字)9798331519094

ISBN: (纸本)9798331519100

Effective management of burn patients in the early stages of treatment is crucial for ensuring survival and optimal recovery. A key element of this process is proper fluid resuscitation, which is essential for maintaining organ function and preventing potentially fatal complications such as shock. Accurate and timely assessment of fluid needs, depending on the Total Body Surface Area (TBSA) affected and the patient’s Hourly Urine Output (HUO), is therefore critical. To address these challenges in burn care, this research introduces a modern web application specifically designed for healthcare providers. The application modern technologies, including Spring Boot, React, ***, MySQL Database and a Java fuzzy logic library, to implement fuzzy logic design and modeling based on the Rule of Nines. This application facilitates rapid analysis of burn extent and provides continuous 24-hour monitoring. By offering accurate, hourly recommendations for fluid resuscitation rates, the tool significantly enhances decision-making in critical care settings. The application includes secure doctor login functionality, allowing healthcare professionals to manage patient data efficiently. Patient information is stored in a database for real-time access and ongoing monitoring. The user-friendly interface allows for seamless data entry and quick interpretation of results, making it highly practical in high-pressure emergency situations.

关键词： Fuzzy logic Java Fluids Accuracy Databases Medical services Real-time systems Libraries Monitoring Surface treatment

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Deep Image Clustering by Spiking Neural Networks

Deep Image Clustering by Spiking Neural Networks

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2023 IEEE Applied Imagery Pattern Recognition Workshop, AIPR 2023

作者： Mahyari, Arash Aliakbarpour, Hadi PensacolaFL United States University of West Florida Department of Intelligent Systems and Robotics PensacolaFL United States Saint Louis University Department of Computer Science St. LouisMO United States

ISBN: (纸本)9798350359527

Neuromorphic cameras, or event cameras, are biologically-inspired sensors that detect changes in illumination at a pixel level, different from traditional cameras where each pixel independently and asynchronously outputs when it senses illumination changes. The neuromorphic cameras exhibit high-Temporal resolution and dynamic range, useful in various applications. Spiking Neural Networks (SNNs), mimicking biological neurons, are efficient in processing neuromorphic images due to their event-driven, low-power nature. However, training SNNs is challenging because of the non-differentiability of neuron models which require different optimization techniques. Inspired by recent works on unsupervised deep clustering in conventional deep learning, we introduce a novel deep clustering algorithm that employs SNNs to extract and group visual features from neuromorphic images into clusters. It utilizes an SNN feature extractor for neuromorphic images, grouping the extracted features using K-means clustering. This algorithm, which doesn't require pre-Trained SNN weights, alternates between cluster updates and SNN weight adjustments. The extracted feature vectors in SNN are clustered and used as pseudo-labels for supervised training of the SNN extractor. The performance of the proposed algorithm is evaluated on two datasets of MNIST and NMNIST, and its effectiveness is assessed using the Normalized Mutual Information (NMI) metric. The performance of our SNN system with neuromorphic images, while marginally below its counterparts of ANNs with traditional images, demonstrates considerable potential. © 2023 IEEE.

关键词： Cameras

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Overview of Energy Harvesting and Sustainability in Smart Cities 3

Overview of Energy Harvesting and Sustainability in Smart Ci...

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3rd International Conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Salama, Ramiz Altrjman, Chadi Al-Turjman, Fadi Yadav, Satya Prakash Vats, Satvik Ai and Robotics Institute Research Center for Ai and IoT Near East University Department of Computer Engineering Near East Boulevard TRNC Mersin 10 Nicosia99138 Turkey Waterloo University Department of Chemical Engineering ONN2L 3G1 Canada Ai and Robotics Institute Near East University Artificial Intelligence Engineering Dept Mersin10 Nicosia Turkey Department of Computer Science and Engineering Greater Noida201306 India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350330724

Sustainability is a key factor in the context of smart cities. In smart cities, promoting sustainable energy is one strategy for achieving sustainability and lowering greenhouse gas emissions. Different energy sources are needed to meet the need for affordable and dependable electrical energy, where the environmental impact typically outweighs the cost of generation. In order to increase sustainability in the electrical industry, smart cities are examined in this article. The methodological strategy for this involved conducting a systematic literature review utilizing the PRISMA procedure. 154 journal articles were examined in-depth for this review. Energy efficiency, renewable energy, and energy and urban planning were the themes that the results were organized into. The results of the study showed that: (a) there is a global academic publication landscape for research on smart cities and energy sustainability;(b) publications are unbalanced when comparing the results of studies on the energy use intensity of different continents to those on the energy sustain ability of smart cities;and (c) there is a strong focus on technology-related issues related to energy sustainability, efficiency, and renewables topics in the literature, but much less attention is given to these issues. Urban and energy authorities are informed by the insights produced, and scholars are given ideas for future research directions. © 2023 IEEE.

关键词： Smart city

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Hector UI: A Flexible Human-Robot User Interface for (Semi-)Autonomous Rescue and Inspection Robots

Hector UI: A Flexible Human-Robot User Interface for (Semi-)...

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IEEE International Workshop on Safety, Security, and Rescue robotics (SSRR)

作者： Stefan Fabian Oskar von Stryk Computer Science Department Simulation Systems Optimization and Robotics Group Technical University of Darmstadt Germany

The remote human operator's user interface (UI) is an important link to make the robot an efficient extension of the operator's perception and action. In rescue applications, several studies have investigated the design of operator interfaces based on observations during major robotics competitions or field deployments. Based on this research, guidelines for good interface design were empirically identified. The investigations on the UIs of teams participating in competitions are often based on external observations during UI application, which may miss some relevant requirements for UI flexibility. In this work, we present an open-source and flexibly configurable user interface based on established guidelines and its exemplary use for wheeled, tracked, and walking robots. We explain the design decisions and cover the insights we have gained during its highly successful applications in multiple robotics competitions and evaluations. The presented UI can also be adapted for other robots with little effort and is available as open source.

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Heterogeneous Wireless Access Networks for IoT and E-Health-A Survey 3

Heterogeneous Wireless Access Networks for IoT and E-Health-...

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3rd International Conference on Advancement in Electronics and Communication Engineering, AECE 2023

ISBN: (纸本)9798350330724

In a heterogeneous wireless environment, there are many different radio access technologies (RATs), such as Wi-Fi and 2G, 3G, 4G, and 5G, which each have a different degree of coverage and processing power to meet various service requirements. A mobile user may have access to various access networks in such a situation. On the PC of each user, numerous programs with varied Quality of Service (QoS) requirements can operate simultaneously. It would be advantageous for a multi-interface terminal to use two or more interfaces simultaneously in order to improve performance. However, using multiple networks at once could use up more energy than just using one interface. Therefore, energy use must to be taken into account when analyzing the Flow/Interface Relationship (FIA). This paper presents a novel method for choosing the ideal FIA that achieves the best trade-off between all the characteristics taken into account, dubbed Smart Tabu Search (STS). STS considers user preferences, network circumstances, network expenses, application QoS specifications, and battery life of mobile devices. We use simulations and testbed experiments to validate our concept. Professionals are now able to diagnose and monitor patients remotely because to the growing use of healthcare monitoring devices. One of the most frequent occurrences that affects the reliability of information transmission in any network is congestion, which is defined as the unchecked increase in traffic relative to network capacity. With the use of a mesh network, wireless sensors, and some of the most significant models for vital signs, the article aims to provide a realistic simulation environment for a healthcare system. The simulator environment is a helpful tool for assessing the dependability and effectiveness of the healthcare system in a realistic setting. However, the system is not appropriate for real-time applications due to the sluggish network adaption caused by the end-to-end based traffic regulation deci

关键词： Electrocardiograms

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Cognitive Approach to Hierarchical Task Selection for Human-Robot Interaction in Dynamic Environments

Cognitive Approach to Hierarchical Task Selection for Human-...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Syed Tanweer Shah Bukhari Bashira Akter Anima David Feil-Seifer Wajahat Mahmood Qazi Cognitive Robotics Group Faculty of IT and CS University of Central Punjab Lahore Pakistan Department of Computer Science Intelligent Machines & Robotics Group COMSATS University Islamabad Pakistan Department of Computer Science & Engineering Socially Assistive Robotics Group University of Nevada Reno Reno NV USA

In an efficient and flexible human-robot collaborative work environment, a robot team member must be able to recognize both explicit requests and implied actions from human users. Identifying “what to do” in such cases requires an agent to have the ability to construct associations between objects, their actions, and the effect of actions on the environment. In this regard, semantic memory is being introduced to understand the explicit cues and their relationships with available objects and required skills to make “tea” and “sandwich”. We have extended our previous hierarchical robot control architecture to add the capability to execute the most appropriate task based on both feedback from the user and the environmental context. To validate this system, two types of skills were implemented in the hierarchical task tree: 1) Tea making skills and 2) Sandwich making skills. During the conversation between the robot and the human, the robot was able to determine the hidden context using ontology and began to act accordingly. For instance, if the person says “I am thirsty” or “It is cold outside” the robot will start to perform the tea-making skill. In contrast, if the person says, “I am hungry” or “I need something to eat”, the robot will make the sandwich. A humanoid robot Baxter was used for this experiment. We tested three scenarios with objects at different positions on the table for each skill. We observed that in all cases, the robot used only objects that were relevant to the skill.

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Simple method of failure detection of rotary machines

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Diagnostyka 2021年第4期22卷 17-22页

作者： Bielecki, Andrzej Bielecka, Marzena Jablonski, Adam Staszewski, Wojciech Institute of Computer Science Faculty of Exact and Natural Sciences Pedagogical University in Krakow Podchorazych 2 Krakow30-084 Poland Geoinformatics and Applied Computer Science Faculty of Geology Geophysics and Environmental Protection AGH University of Science and Technology Mickiewicza 30 Krakow30-059 Poland Robotics and Mechatronics Faculty of Mechanical Engineering and Robotics AGH University of Science and Technology Mickiewicza 30 Krakow30-059 Poland

In the paper a simple unsupervised monitoring method of rotary machines is proposed. The method consists of three stages multi-reference preliminary analysis of the vibration signals, auto-reference preliminary analysis and probabilistic analysis of the signals. The method was tested by using signals from eight simulated machines. The efficiency of the method has been positively verified. © 2021 Polish Society of Technical Diagnostics. All rights reserved.

关键词： Vibration analysis

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Input and Editing of Force Profiles of In-Contact Robot Motions via a Touch Graphical User Interface

Input and Editing of Force Profiles of In-Contact Robot Moti...

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IEEE International Conference on Robotic Computing (IRC)

作者： Johannes Hartwig Pascal Ruppert Dominik Henrich Chair for Applied Computer Science III (Robotics and Embedded Systems) University of Bayreuth Bayreuth Germany

Various automation tasks require the precise specification of forces/torques over time and space to be applied to the environment. Traditionally, only experts can provide such specifications, contrasting the need for intuitive robot programming in small and medium-sized enterprises. This paper presents a concept for extending kinesthetic robot programming to allow users to program motions in contact with the environment. In this context, four novel input methods enable non-experts to input and edit force/torque profiles graphically via a touch device as a function graph. A user study compares the input methods regarding duration, accuracy, and workload. In addition, the system's intuitiveness and usability for programming in-contact motions are evaluated. Even for a small sample set (N = 20), the evaluation of the System Usability Scale (SUS) showed a high median result (82.5). Thus, the promising results indicate that the presented programming system is usable and intuitive for non-experts.

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Enhancing Multi-Drone Coordination for Filming Group Behaviours in Dynamic Environments

arXiv

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arXiv 2023年

作者： Rauniyar, Aditya Li, Jiaoyang Scherer, Sebastian The Robotics Institute School of Computer Science Carnegie Mellon University PittsburghPA United States

Multi-Agent Path Finding (MAPF) is a fundamental problem in robotics and AI, with numerous applications in real-world scenarios. One such scenario is filming scenes with multiple actors, where the goal is to capture the scene from multiple angles simultaneously. Here, we present a formation-based filming directive of task assignment followed by a Conflict-Based MAPF algorithm for efficient path planning of multiple agents to achieve filming objectives while avoiding collisions. We propose an extension to the standard MAPF formulation to accommodate actor-specific requirements and constraints. Our approach incorporates Conflict-Based Search, a widely used heuristic search technique for solving MAPF problems. We demonstrate the effectiveness of our approach through experiments on various MAPF scenarios in a simulated environment. The proposed algorithm enables the efficient online task assignment of formation-based filming to capture dynamic scenes, making it suitable for various filming and coverage applications. Copyright © 2023, The Authors. All rights reserved.

关键词： Multipurpose robots

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