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Online Damage Recovery for Physical Robots with Hierarchical Quality-Diversity

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arXiv 2022年

作者： Allard, Maxime Smith, Simón C. Chatzilygeroudis, Konstantinos Lim, Bryan Cully, Antoine Adaptive and Intelligent Robotics Lab Imperial College London United Kingdom Computer Engineering and Informatics Department University of Patras Greece

In real-world environments, robots need to be resilient to damages and robust to unforeseen scenarios. Quality-Diversity (QD) algorithms have been successfully used to make robots adapt to damages in seconds by leveraging a diverse set of learned skills. A high diversity of skills increases the chances of a robot to succeed at overcoming new situations since there are more potential alternatives to solve a new task. However, finding and storing a large behavioural diversity of multiple skills often leads to an increase in computational complexity. Furthermore, robot planning in a large skill space is an additional challenge that arises with an increased number of skills. Hierarchical structures can help reducing this search and storage complexity by breaking down skills into primitive skills. In this paper, we introduce the Hierarchical Trial and Error algorithm, which uses a hierarchical behavioural repertoire to learn diverse skills and leverages them to make the robot adapt quickly in the physical world. We show that the hierarchical decomposition of skills enables the robot to learn more complex behaviours while keeping the learning of the repertoire tractable. Experiments with a hexapod robot show that our method solves a maze navigation tasks with 20% less actions in simulation, and 43% less actions in the physical world, for the most challenging scenarios than the best baselines while having 78% less complete failures. © 2022, CC BY.

关键词： Robot programming

Movement Sonification of Familiar Music to Support the Agency of People with Chronic Pain 25

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Movement Sonification of Familiar Music to Support the Agenc...

2025 CHI Conference on Human Factors in Computing Systems, CHI 2025

作者： Potapov, Kyrill Gold, Nicolas Olugbade, Temitayo De C Williams, Amanda C Overbeck, Christopher Dieter Lynch, Danielle Nygren, Minna Berthouze, Nadia UCL Interaction Centre University College London London United Kingdom UCL Computer Science University College London London United Kingdom School of Engineering and Informatics University of Sussex Brighton United Kingdom Department of Clinical Educational & Health Psychology University College London London United Kingdom UCL Computer Science London United Kingdom His Majesty's Civil Service London United Kingdom UCL Interaction Centre UCL London United Kingdom

ISBN: (纸本)9798400713941

FFAME (Filtering Familiar Audio for Movement Exploration) is a novel sonification framework aiming to facilitate movement in individuals with chronic back pain. Our personalised, music-based approach contrasts and extends prior work with predetermined tonal sonification. FFAME progressively filters selected music based on angles of the trunk. Through a qualitative analysis of reported experience of 15 participants with chronic pain and 5 physiotherapists, we identify how sonification parameters and musical characteristics affect movement and meaning-making. Music-based movement sonification proved impactful across multiple dimensions: (1) encouraging movement, (2) escaping pain-related rumination, (3) externalizing pain experiences, and (4) scaffolding physical activities. Drawing on enactivism and related philosophies, the study highlights how the semantic indeterminacy of music, combined with real-time movement sonification, created a rich, open-ended environment that supported user agency and exploration. Sonification for pain management can be creative and expressive, enabling people with pain to extend challenging movements and build movement confidence. © 2025 Copyright held by the owner/author(s).

关键词： Time and motion study

Hierarchical Quality-Diversity for Online Damage Recovery

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arXiv 2022年

作者： Allard, Maxime Smith, Simón C. Chatzilygeroudis, Konstantinos Cully, Antoine Adaptive and Intelligent Robotics Lab Imperial College London United Kingdom Computer Engineering and Informatics Department University of Patras Greece

Adaptation capabilities, like damage recovery, are crucial for the deployment of robots in complex environments. Several works have demonstrated that using repertoires of pre-trained skills can enable robots to adapt to unforeseen mechanical damages in a few minutes. These adaptation capabilities are directly linked to the behavioural diversity in the repertoire. The more alternatives the robot has to execute a skill, the better are the chances that it can adapt to a new situation. However, solving complex tasks, like maze navigation, usually requires multiple different skills. Finding a large behavioural diversity for these multiple skills often leads to an intractable exponential growth of the number of required solutions. In this paper, we introduce the Hierarchical Trial and Error algorithm, which uses a hierarchical behavioural repertoire to learn diverse skills and leverages them to make the robot more adaptive to different situations. We show that the hierarchical decomposition of skills enables the robot to learn more complex behaviours while keeping the learning of the repertoire tractable. The experiments with a hexapod robot show that our method solves maze navigation tasks with 20% less actions in the most challenging scenarios than the best baseline while having 57% less complete failures. © 2022, CC BY.

关键词： Robots

Efficient Chrome Extension for Phishing Detection Using Machine Learning Techniques

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arXiv 2024年

作者： Thaçi, Leand Halili, Arbnor Vishi, Kamer Rexha, Blerim Faculty of Electrical and Computer Engineering University of Prishtina Kodra e Diellit p.n. Prishtina10000 Serbia Department of Informatics University of Oslo Gaustadalléen 23B OsloN-0373 Norway

The growth of digitalization services via web browsers has simplified our daily routine of doing business. But at the same time, it has made the web browser very attractive for several cyber-attacks. Web phishing is a well-known cyberattack that is used by attackers camouflaging as trustworthy web servers to obtain sensitive user information such as credit card numbers, bank information, personal ID, social security number, and username and passwords. In recent years many techniques were developed to identify the authentic web pages that user visits and warn them when the webpage is a phish. In this paper, we have developed an extension for Chrome as the most favorite web browser, that will serve as a middleware between the user and phishing websites. The Chrome extension named "NoPhish" shall identify a phishing webpage based on several Machine Learning techniques. We have used the training dataset from "PhishTank" and extracted the 22 most popular features as rated by Alexa database. The training algorithms used are Random Forest, Support Vector Machine, and k-Nearest Neighbor. The performance results show that Random Forest delivers the best precision. © 2024, CC BY.

关键词： Phishing

Developing Instruments for Digital Talent Competence Using Partial Least Square-Based Models 11

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Developing Instruments for Digital Talent Competence Using P...

11th International Conference on Cyber and IT Service Management, CITSM 2023

作者： Wahyudi, Mochamad Chakim, Mochamad Heru Riza Henderi Sudaryono Si, Muhamad Viktor A Saputra, Dimas Bagus Rahardja, Reymund Master of Computer Science University of Bina Sarana Informatika Tangerang Indonesia University of Raharja Master of Retail Management Tangerang Indonesia University of Raharja Master of Informatics Engineering Tangerang Indonesia University of Raharja Master of Digital Business Tangerang Indonesia University of Raharja Department of Information Technology Tangerang Indonesia University of Raharja Department of Digital Business Tangerang Indonesia

ISBN: (纸本)9798350305968

Research on measuring digital talent competencies using explainable artificial intelligence is lacking in depth. The study aimed to address this gap by developing a reliable and valid measurement instrument for digital talent. SmartPLS 4.0 was employed for calculations and quality assessment. The measurement model was assessed from both reflective and formative perspectives, using Google Forms to gather responses from 600 participants. The 60 questionnaire items exhibited high validity and reliability, as evidenced by loading factors and composite reliability exceeding 0.70. Direct effects were found in various competencies: adaptability and flexibility had a 0.744 effect on learning dexterity, achievement orientation showed a 0.782 effect on innovative creation skills, customer service orientation had a 0.810 effect on digital networking, and digital communication skills exhibited a 0.824 effect on continual improvement. The measurement model met various criteria for reliability and validity, including loading factors, composite reliability, average variance extracted, cross loadings, Fornell Lacker Criterion, and Heterotrait Monotrait Ratio. These findings supported the acceptance of the measurement model's quality and validity. SmartPLS analysis yielded an average communality of 0.624 and an average R Square of 0.592, resulting in a GoF index of 0.608. This GoF index, according to Wetzel et al. (2018), falls in the high fit category, indicating the model's appropriateness for measuring digital talent competencies. In summary, the study successfully developed a robust measurement model for digital talent competencies using explainable artificial intelligence and demonstrated its high fit and reliability for assessing digital talent in various contexts. © 2023 IEEE.

关键词： Reliability

Experimental Analysis of a Self-Coherent M-QAM Receiver by Means of Recurrent Optical Spectrum Slicing and Direct Detection

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arXiv 2025年

作者： Sozos, Kostas Da Ros, Francesco Yankov, Metodi P. Deligiannidis, Stavros Sarantoglou, George Mesaritakis, Charis Bogris, Adonis University of West Attica Dept. of Informatics and Computer Engineering. Aghiou Spiridonos Egaleo Athens12243 Greece University of West Attica Dept. of Biomedical Engineering Aghiou Spiridonos Egaleo Athens12243 Greece Dept. of Electrical and Photonics Engineering Technical University of Denmark Kgs. LyngbyDK-2800 Denmark

High order modulation formats constitute the most prominent way for increasing spectral efficiency in transmission systems. Coherent transceivers that support such higher order formats require heavy digital signal processing (DSP), which increases the power consumption of coherent pluggables, well above the intensity modulation and direct detection (IM/DD) counterparts. Self-coherent or phase retrieval methods have emerged as potential solutions, trying to combine the merits of coherent technology with the simplicity of direct detection. In this work, we experimentally demonstrate the reception of quadrature amplitude modulation (QAM) modulation formats based on direct detection aided by the recurrent optical spectrum slicing (ROSS) photonic accelerator, utilizing minimal DSP and low modulator driving voltages. We experimentally demonstrate 32 Gbaud QAM-4/16 for 25 km, 50 km and 75 km in the C-band aided by a linear digital equalization and the use of programmable photonics as recurrent optical spectrum slicers. We showcase successful detection with driving swings below Vπ/3 in contrast to the full swing required by conventional coherent transceivers. We further improve the system performance utilizing geometric constellation shaping. Finally, we explore the potential power consumption improvement for the next-generation 1.6T pluggables, showcasing over 40% reduction with respect to the most lightweight state of the art coherent solutions reported in literature. © 2025, CC BY.

关键词： Quadrature amplitude modulation

Mobile-based Network Monitoring System Using Zabbix and Telegram 3

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Mobile-based Network Monitoring System Using Zabbix and Tele...

3rd International Conference on computer and informatics engineering, IC2IE 2020

作者： Mardiyono, Anggi Sholihah, Walidatush Hakim, Faisal Jakarta State Polytechnic Department of Computer and Informatics Engineering Depok Indonesia IPB University Computer Engineering Vocational School Bogor Indonesia

ISBN: (纸本)9781728182476

Network monitoring system is a system that works to observe and monitor the situation on a running computer network. Network monitoring is very important to keep the network running well and to know the current condition of the network. Generally, network monitoring requires the administrator to stay and to keep an eye in front of the monitor screen to find out any problems that occur. The administrator or the operator also need network notification problem in real time. This makes the network supervision process very dependent on time and place. This research develops a system for helping administrator or network operator to monitor the network using mobile phone at any time and any place. This monitoring process in this paper using Zabbix. In monitoring the computer network is also needed a notification. The notification of the problem in the network will be sent using Telegram Messenger. This research was conducted in Indonesian Internet Service Provider Association (APJII). The method used in this research is Network Development Life Cycle (NDLC). © 2020 IEEE.

关键词： Monitoring

Distributed management of patient data-sharing informed consents for clinical research

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computers in Biology and Medicine 2024年 180卷 108956页

作者： Pham, Anh Edelson, Maxim Nouri, Armin Kuo, Tsung-Ting UCSD Health Department of Biomedical Informatics University of California San Diego La Jolla CA United States UCSD Department of Computer Science and Engineering University of California San Diego La Jolla CA United States Department of Biomedical Engineering Fu Foundation School of Engineering Columbia University New YorkNY United States Department of Biomedical Informatics and Data Science School of Medicine Yale University New HavenCT United States Department of Surgery School of Medicine Yale University New HavenCT United States

Background: The consent protocol is now a critical part in the overall orchestration of clinical research. We aimed to demonstrate the feasibility of an Ethereum-based informed consent system, which includes an immutable and automated channel of consent matching, to simultaneously assure patient privacy and increase the efficiency of researchers’ data access. Method: We simulated a multi-site scenario, each assigned 10000 consent records. A consent record contained one patient's data-sharing preference with regards to seven data categories. We developed a blockchain-based infrastructure with a smart contract to record consents on-chain, and to query consenting patients corresponding to specific criteria. We measured our system's recording efficiency against a baseline design and verified accuracy by testing an exhaustive list of possible queries. Results: Our method achieved ∼3–4% lead with an average insertion speed of ∼2 s per record per node on either a 3-, 4- or 5-node network, and 100 % accuracy. It also outperformed other solutions in external validation. Discussion: The speed we achieved is reasonable in a real-world system under the realistic assumption that patients may not change their minds too frequently, with the added benefit of immutability. Furthermore, the per-insertion time did improve slightly as the number of network nodes increased, attesting to the benefit of node parallelism as it suggests no attrition of insertion efficiency due to scale of nodes. Conclusions: Our work confirms the technical feasibility of a blockchain-based consent mechanism, assuring patients with an immutable audit trail, and providing researchers with an efficient way to reach their cohorts. © 2024

关键词： Clinical research

Real-Time Ball Speed Stabilization Acquisition using Low Pass Filter on Robot Soccer ERSOW

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Real-Time Ball Speed Stabilization Acquisition using Low Pas...

2020 International Conference on computer engineering, Network, and Intelligent Multimedia, CENIM 2020

作者： Nurrohmah, Erna Alfi Priambudi, Renardi Adryantoro Ariyadi, Bagus Nugraha Deby Wibowo, Iwan Kurnianto Dewantara, Bima Sena Bayu Politeknik Elektronika Negeri Surabaya Departement of Informatics and Computer Engineering Surabaya Indonesia

ISBN: (纸本)9781728182834

This paper presents the acquisition and stabilization of the ball speed data on the Robot Soccer ERSOW. The skills such as receiving and passing ball needs a good quality of ball speed data, but the ball speed data on robot ERSOW is very unstable. However, we argued that this unstable ball speed data can be minimized using the Low Pass Filter (LPF). The LPF method can reduce the average ball speed changing rate on the speed-x data around 4.57 cm/s on LPF cutoff value 0.75, 4.9 cm/s on cutoff value 0.8, and 8.6 cm/s on cutoff value 0.99. Furthermore, the speed-y is changing from 43.02 cm/s into 12.05 cm/s on LPF cutoff value 0.75, 14.02 cm/s on LPF cutoff value 0.8, and 17.7 cm/s on LPF cutoff value 0.99. The result is quite good because the smaller value of the average speed changing rate indicates the data is more stable. © 2020 IEEE.

关键词： Low pass filters