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14th International Conference on Bioinformatics and Computational Biology, BICOB 2022

作者： Zaman, Ahmed Bin De Jong, Kenneth Shehu, Amarda Dept. of Computer Science George Mason University FairfaxVA22030 United States Center for Advancing Human-Machine Partnerships George Mason University United States Dept. of Bioengineering George Mason University United States School of Systems Biology George Mason University United States

Deep learning research, from ResNet to AlphaFold2, convincingly shows that deep learning can predict the native conformation of a given protein sequence with high accuracy. Accounting for the plasticity of protein molecules remains challenging, and powerful algorithms are needed to sample the conformation space of a given amino-acid sequence. In the complex and high-dimensional energy surface that accompanies this space, it is critical to explore a broad range of areas. In this paper, we present a novel evolutionary algorithm that guides its optimization process with a memory of the explored conformation space, so that it can avoid searching already explored regions and search in the unexplored regions. The algorithm periodically consults an evolving map that stores already sampled non-redundant conformations to enhance exploration during selection. Evaluation on diverse datasets shows superior performance of the algorithm over the state-of-the-art algorithms. © 2022, EasyChair. All rights reserved.

关键词： Conformations

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Analysis of AlphaFold2 for Modeling Structures of Wildtype and Variant Protein Sequences 14th

Analysis of AlphaFold2 for Modeling Structures of Wildtype a...

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14th International Conference on Bioinformatics and Computational Biology, BICOB 2022

作者： Kabir, Anowarul Inan, Toki Tahmid Shehu, Amarda Dept. of Computer Science George Mason University FairfaxVA22030 United States Center for Advancing Human-Machine Partnerships George Mason University United States Dept. of Bioengineering George Mason University United States School of Systems Biology George Mason University United States

ResNet and, more recently, AlphaFold2 have demonstrated that deep neural networks can now predict a tertiary structure of a given protein amino-acid sequence with high accuracy. This seminal development will allow molecular biology researchers to advance various studies linking sequence, structure, and function. Many studies will undoubtedly focus on the impact of sequence mutations on stability, fold, and function. In this paper, we evaluate the ability of AlphaFold2 to predict accurate tertiary structures of wildtype and mutated sequences of protein molecules. We do so on a benchmark dataset in mutation modeling studies. Our empirical evaluation utilizes global and local structure analyses and yields several interesting observations. It shows, for instance, that AlphaFold2 performs similarly on wildtype and variant sequences. The placement of the main chain of a protein molecule is highly accurate. However, while AlphaFold2 reports similar confidence in its predictions over wildtype and variant sequences, its performance on placements of the side chains suffers in comparison to main-chain predictions. The analysis overall supports the premise that AlphaFold2-predicted structures can be utilized in further downstream tasks, but that further refinement of these structures may be necessary. © 2022, EasyChair. All rights reserved.

关键词： Forecasting

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Applying grid world based reinforcement learning to real world collaborative transport

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Procedia computer science 2024年 232卷 388-396页

作者： Alexander Hämmerle Christoph Heindl Gernot Stübl Jenish Thapa Edoardo Lamon Andreas Pichler Profactor GmbH Im Stadtgut D1 4407 Steyr-Gleink Austria Human-Robot Interfaces and Interaction Istituto Italiano di Tecnologia Via S. Quirico 19d 16163 Genoa Italy Dept. of Information Engineering and Computer Science Universita` di Trento Via Sommarive 9 Povo Italy

Motivated by transportation tasks on construction sites, this contribution deals with an AI-driven approach to human-robot collaborative transportation. An essential part of the considered problem is navigating the robot to the object to be transported, in the presence of other moving items like the human moving to the object. Robot navigation is tackled with reinforcement learning, and the impact of randomness in the other moving items’ behaviour on the robot's training performance is investigated. Results show that the move failure rate of the trained robot policy increases, when the behavioural patterns in the human's movements are disturbed by randomness. On the other hand, when both human and robot are connected to the object, the navigation problem is delegated to the human, which guides the compound human-object-robot to the goal location.

关键词： collaborative transportation reinforcement learning robot navigation

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EEG Context Fusion for AI-Based Object Detection and Drone Navigation in Situationally Aware Brain-computer Interfaces

EEG Context Fusion for AI-Based Object Detection and Drone N...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： T. Warren de Wit Vineetha Menon Nathan Tenhundfeld Thomas Davis Dept. of Computer Science University of Alabama Huntsville Huntsville USA Dept. of Psychology University of Alabama Huntsville Huntsville USA Human Systems Integration Division DEVCOM Data and Analysis Center Huntsville USA

We are interested in the utility that artificially intelligent mobile systems such as drones offer to personnel in fast-paced situations such as hostage rescue and disaster relief for real-time situational awareness. Ideally, these assistive systems place no additional cognitive or physical burden on their user; rather, they should respond to the user’s intent with minimal physical and cognitive burden. To this end, brain-computer interface (BCI) and in particular electroencephalography (EEG) offers a novel way to capture intent. EEG-based drone control has been explored, but typically relies on the domain of motor imagery (MI), which still requires somewhat-manual drone piloting for micro directional movement, adding cognitive burden. We propose leveraging the robust computer-vision based AI that exists on modern drones to use objects as waypoints and fly mostly autonomously, with EEG in an object recognition paradigm for passively selecting the waypoint. While existing techniques for EEG object recognition-including steady-state visually evoked potentials (SSVEP), rapid serial visual presentation (RSVP), and eye tracking - rely on “marked” input or a controlled environment, we need one that will work on passive objects. In this work, we propose merging available scene imagery in a vision network with deep-learning based EEG processing to achieve passive intent recognition. The proposed context-scene fusion for a situational awareness paradigm presents accuracy in the same ranges as existing object recognition without requiring SSVEP, RSVP, eye tracking, or MI techniques and serves as proof-of-concept for this approach to real-world BCI applications.

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Automatic interaction and Activity Recognition from Videos of human Manual Demonstrations with Application to Anomaly Detection

arXiv

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arXiv 2023年

作者： Merlo, Elena Lagomarsino, Marta Lamon, Edoardo Ajoudani, Arash Human-Robot Interfaces and Interaction Laboratory Istituto Italiano di Tecnologia Genoa Italy Dept. of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy Dept. of Electronics Information and Bioengineering Politecnico di Milano Milan Italy Dept. of Information Engineering and Computer Science University of Trento Trento Italy

This paper presents a new method to describe spatio-temporal relations between objects and hands, to recognize both interactions and activities within video demonstrations of manual tasks. The approach exploits Scene Graphs to extract key interaction features from image sequences while simultaneously encoding motion patterns and context. Additionally, the method introduces event-based automatic video segmentation and clustering, which allow for the grouping of similar events and detect if a monitored activity is executed correctly. The effectiveness of the approach was demonstrated in two multi-subject experiments, showing the ability to recognize and cluster hand-object and object-object interactions without prior knowledge of the activity, as well as matching the same activity performed by different subjects. Copyright © 2023, The Authors. All rights reserved.

关键词： Anomaly detection

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Automatic interaction and Activity Recognition from Videos of human Manual Demonstrations with Application to Anomaly Detection

Automatic Interaction and Activity Recognition from Videos o...

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IEEE International Workshop on Robot and human Communication (ROMAN)

作者： Elena Merlo Marta Lagomarsino Edoardo Lamon Arash Ajoudani Human-Robot Interfaces and Interaction Laboratory Istituto Italiano di Tecnologia Genoa Italy Dept. of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy Dept. of Electronics Information and Bioengineering Politecnico di Milano Milan Italy Dept. of Information Engineering and Computer Science University of Trento Trento Italy

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Development of a compact mouse retinal imaging system using spectral domain optical coherence tomography (SD-OCT) with a full field stimulation channel for recording fast optoretinograms (ORGs) 34

Development of a compact mouse retinal imaging system using ...

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Ophthalmic Technologies XXXIV 2024

作者： Jo, Hang Chan Pijewska, Ewelina Meleppat, Ratheesh K. Jonnal, Ravi S. Kim, Dae Yu Zawadzki, Robert J. Department of Electrical and Computer Engineering Inha University 100 Inha-ro Michuhol-gu Incheon22212 Korea Republic of Dept. of Ophthalmology and Vision Science UC Davis Eye Center SacramentoCA95817 United States UC Davis Eye-Pod Small Animal Ocular Imaging Laboratory Department of Cell Biology and Human Anatomy University of California Davis 4320 Tupper Hall DavisCA95616 United States

ISBN: (纸本)9781510669079

While the a-wave of mouse electroretinogram (ERG) occurs within 50 milliseconds after exposure to light, the optoretinogram (ORG) slower than a 20Hz sampling rate could face limitations in observing immediate morphological changes from the retina. In this study, we develop a compact custom-built mouse ORG system based on spectral domain optical coherence tomography (SD-OCT) for 100Hz~1KHz B-scan rates comprised of 100 kHz A-scans. All the optics of the developed ORG system are designed on a 24 x 24 inches optical breadboard to move easily as well as to combine with the ERG system in a dark room. Without using a fundus camera, the OCT system provides en-face images from high-pass filtering and square of the OCT spectral signal for mouse retinal positioning in-vivo before acquiring ORG data. The 490nm LED for light stimulus is generated to make uniform illumination at the mouse retina using the Maxwellian view method. The common path of the OCT scanning light and the visible LED is built with achromatic doublet lens combinations based on optical simulation with Opticstudio® . The developed compact ORG system can not only observe light-evoked responses with 1~10 milliseconds but also be used for the studies of correlations between ORG and ERG in the mouse retina. © 2024 SPIE.

关键词： Optical tomography

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Spatial Referencing for Anywhere, Anytime Augmented Reality

Spatial Referencing for Anywhere, Anytime Augmented Reality

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Yuan Li Center for Human-Computer Interaction and Dept. of Computer Science Virginia Tech

ISBN: (数字)9781728165325

ISBN: (纸本)9781728165332

Augmented Reality (AR) systems can effectively enhance collaboration in the real world by providing useful spatial cues through virtual overlays. In particular, AR can be used to facilitate referencing a location in space as required in many collaborative activities. However, the goal of supporting spatial referencing anywhere at any time is hindered by issues with current AR technology, such as the lack of a precise environment model, unreliable tracking, and difficulty in synchronizing among different devices. This paper proposes a research agenda that innovates in the domain of interaction techniques for spatial referencing for everywhere AR.

关键词： Biological system modeling Three-dimensional displays Collaboration Augmented reality Visualization Reliability Computational modeling

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Realizing right to education and SDG 4 in the Indonesia - Timor leste border: The role of the state-owned ICT enterprises 2021

Realizing right to education and SDG 4 in the Indonesia - Ti...

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6th International Conference on Distance Education and Learning, ICDEL 2021

作者： Stefanus Mere, Winibaldus Fios, Frederikus Siregar, Christian Pane, Murty Magda Lake, Silverius Constantino Yohanes Maria International Human Rights Law Politic Economy and Human Dignity Human Rights Nanzan University Nagoya Campus 18 Yamazato-cho Showa-ku Nagoya Aichi Nagoya466-8673 Japan Character Building Development Center School of Computer Science Dept. of Computer Science Bina Nusantara University Jl. Kemanggisan Ilir III No.45Barat Jakarta Indonesia

ISBN: (纸本)9781450390033

This paper aims at providing a theoretical framework of the significance of (1) virtual teaching and learning activities through information and communication technology (ICT) to achieve the full realization of right to education in the Indonesia - Timor Leste border and (2) the role of State-owned enterprises (SOEs) engaging in ICT for investing in infrastructure for virtual teaching and learning to achieve the equal quality education (SDGs4). The relevance of studying this theoretical framework arises from the assumption that digitally mediated learning dan teaching can provide a useful alternative to address the problems of the lack of teachers that have been facing by many remote communities in the border areas. Using literature review and secondary sources, the paper argues that the SOEs' investment in ICT learning and teaching is imperative. However, the appropriateness and effectiveness of its method and substance that will lead to a meaningful realization of SDG4 will be very much dependent on: 1) the State's and SOEs' knowledge about the connection between human rights and SDGs;2) clear educational objectives, conducive pedagogical environment, dynamic learning and teaching processes and responsive educational governance suitable for digitally mediated education system;and 3) the capability of SOEs engaged in ICT to use SDG4 as an overarching framework to shape, steer, communicate and report their strategies, goals and activities when they invest in digitally mediated education system. © 2021 ACM.

关键词： Investments

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Expanding teacher's creativity during Covid-19 era at timor-leste border area in 2020 2021

Expanding teacher's creativity during Covid-19 era at timor-...

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6th International Conference on Distance Education and Learning, ICDEL 2021

作者： Fios, Frederikus Ff Lake, Silverius Constantino J. Maria Pane, Murty Magda Siregar, Christian Mere, Winibaldus Character Building Development Center School of Computer Science Dept. of Computer Science Bina Nusantara University Jl. Kemanggisan Ilir III No.45 Barat Jakarta Indonesia Character Building Development Center Faculty of Communication Communication Science Bina Nusantara University Jl. Kemanggisan Ilir Iii No.45 Barat Jakarta Indonesia International Human Rights Law Politic Economy and Human Dignity on Human Rights Nanzan University Nagoya Campus Aichi Nagoya Showa Ward Yamazatocho466-8673 Japan

ISBN: (纸本)9781450390033

The life of East Timor residents in the New Settlements becomes a certain problem. The problem of becoming Indonesian makes a certain point to be solved. The problem is about how to handle students creatively in the era of pandemic Covid-19. Objectives of this research consist of some points. (1) To find out teacher's creativity in doing approach to students who are learning at home related to the pandemic Covid-19 era in the border area of Timor-Leste. (2) To seek and to expand models of creativity in the context of teaching from home or school for students who are staying at home in the border of Indonesia and Timor-Leste area. The research method uses qualitative method especially literature studies, contemporary newspaper studies, and survey studies on teacher's creativity in Europe schools. The results of research are: (1) In fact, the technology and creativity are keys to the learning process in the era with the challenges of Covid-19 pandemic. (2) According to the results of the study, students who are learning at home have difficulty accessing the internet. (3) The quality and creativity of teachers need to be considered, expanded, and improved. (4) According to the results of this study, teachers' creative abilities were at a moderate level because teachers were shocked by the spread of Covid-19. © 2021 ACM.

关键词： Students

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