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9th International Joint Conference on Computational Intelligence, IJCCI 2017

作者： Álvarez-Caballero, Antonio Merelo, J.J. Sánchez, Pablo García Fernández-Ares, A. Department of Computer Architecture and Computer Technology University of Granada Spain Department of Computer Science University of Cádiz Spain

ISBN: (纸本)9789897582745

A fast and precise prediction of the outcome of a game is essential for the design of bots that play the game;it can be used either offline as a fast way to design bot strategies or online for conserving resources and conceding defeat or speed up victory, as well as evaluating the consequences of actions. The objective of this paper is predicting the winner of a StarCraft match as soon as possible. This study is done with supervised learning, because a lot of suitable data is available. The main problem of this approach is the big amount of generated data, so it has to be selected and organised properly and be treated with proper tools. A set of six learning algorithms is used, from simpler ones to more complex algorithms. Spark and MLlib are used due to their capabilities to deal with big amounts of data. With the learned models, time of matches are restricted, trying to get a time bound for predicting results. With this approach we get that it is not necessary to play a whole match to predict its winner with high accuracy: with 10 minutes we can predict the outcome with 90% of accuracy. Copyright © 2017 by SCITEPRESS - Science and technology Publications, Lda. All rights reserved.

关键词： Forecasting

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Automated sequence and motion planning for robotic spatial extrusion of 3D trusses

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Construction Robotics 2018年第1期2卷 15-39页

作者： Yijiang Huang Caelan R. Garrett Caitlin T. Mueller Building Technology Program Department of Architecture Massachusetts Institute of Technology Cambridge USA Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge USA

While robotic spatial extrusion has demonstrated a new and efficient means to fabricate 3D truss structures in architectural scale, a major challenge remains in automatically planning extrusion sequence and robotic motion for trusses with unconstrained topologies. This paper presents the first attempt in the field to rigorously formulate the extrusion sequence and motion planning (SAMP) problem, using a CSP encoding. Furthermore, this research proposes a new hierarchical planning framework to solve the extrusion SAMP problems that usually have a long planning horizon and 3D configuration complexity. By decoupling sequence and motion planning, the planning framework is able to efficiently solve the extrusion sequence, end-effector poses, joint configurations, and transition trajectories for spatial trusses with nonstandard topologies. This paper also presents the first detailed computation data to reveal the runtime bottleneck on solving SAMP problems, which provides insight and comparing baseline for future algorithmic development. Together with the algorithmic results, this paper also presents an open-source and modularized software implementation called Choreo that is machine-agnostic. To demonstrate the power of this algorithmic framework, three case studies, including real fabrication and simulation results, are presented.

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Communication lower bound in convolution accelerators

arXiv

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arXiv 2019年

作者： Chen, Xiaoming Han, Yinhe Wang, Yu Center for Intelligent Computing Systems State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Department of Electronic Engineering Tsinghua University Beijing China

In current convolutional neural network (CNN) accelerators, communication (i.e., memory access) dominates the energy consumption. This work provides comprehensive analysis and methodologies to minimize the communication for CNN accelerators. For the off-chip communication, we derive the theoretical lower bound for any convolutional layer and propose a dataflow to reach the lower bound. This fundamental problem has never been solved by prior studies. The on-chip communication is minimized based on an elaborate workload and storage mapping *** in addition design a communication-optimal CNN accelerator architecture. Evaluations based on the 65nm technology demonstrate that the proposed architecture nearly reaches the theoretical minimum communication in a threelevel memory hierarchy and it is computation dominant. The gap between the energy efficiency of our accelerator and the theoretical best value is only 37-87%. Copyright © 2019, The Authors. All rights reserved.

关键词： Acceleration

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Comparing the Design Neurocognition of Mechanical Engineers and Architects: A Study of the Effect of Designer’s Domain

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Proceedings of the Design Society: International Conference on Engineering Design 2019年第1期1卷 1853-1862页

作者： Sonia Liliana da Silva Vieira John S. Gero Jessica Delmoral Valentin Gattol Carlos Fernandes António A. Fernandes INEGI Institute of Science and Innovation in Mechanical and Industrial Engineering Porto Portugal Department of Computer Science and School of Architecture University of North Carolina at Charlotte United States AIT Austrian Institute of Technology Vienna Austria FMUP Faculty of Medicine of the University of Porto Portugal FEUP Faculty of Engineering University of Porto Portugal

New tools from neuroscience allow design researchers to explore design neurocognition. By taking the advantage of EEG's temporal resolution we give up spatial resolution to focus on the performance of time-related design tasks. This paper presents results from an experiment using EEG to measure brain activation to study mechanical engineers and architects to compare their design neurocognition. In this study, we adopted and extended the tasks described in a previous fMRI study of design neurocognition reported in the literature. The block experiment consists of a sequence of 3 tasks: problem solving, basic design and open design using a physical interface. The block is preceded by a familiarizing pre-task using the physical interface and then extended to a fourth task using free-hand sketching. Brainwaves were collected from both mechanical engineers and architects. Results comparing 36 mechanical engineers and architects while designing were produced. These results indicate design cognition differences between the two domains in task-related power between the problem-solving task and the design tasks, in temporal resolution and transformed power.

关键词： Design cognition Research methodologies and methods Human behaviour in design Design domains Design neuroscience

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A sliding window method for detecting corners of openings from terrestrial LiDAr data 13

A sliding window method for detecting corners of openings fr...

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13th 3D GeoInfo Conference 2018

作者： Li, Jiaqiang Xiong, Biao Biljecki, Filip Schrotter, Gerhard ETH Zurich Future Cities Laboratory Singapore-ETH Centre Singapore School of Computer Science and Technology Wuhan University of Technology China Dipper 3D Netherlands Department of Architecture National University of Singapore Singapore City of Zurich Switzerland

Architectural building models (LoD3) consist of detailed wall and roof structures including openings, such as doors and windows. Openings are usually identified through corner and edge detection, based on terrestrial LiDAR point clouds. However, singular boundary points are mostly detected by analysing their neighbourhoods within a small search area, which is highly sensitive to noise. In this paper, we present a global-wide sliding window method on a projected façade to reduce the influence of noise. We formulate the gradient of point density for the sliding window to inspect the change of façade elements. With derived symmetry information from statistical analysis, border lines of the changes are extracted and intersected generating corner points of openings. We demonstrate the performance of the proposed approach on the static and mobile terrestrial LiDAR data with inhomogeneous point density. The algorithm detects the corners of repetitive and neatly arranged openings and also recovers angular points within slightly missing data areas. In the future we will extend the algorithm to detect disordered openings and assist to façade modelling, semantic labelling and procedural modelling. © Authors 2018. CC BY 4.0 License.

关键词： Edge detection

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An Efficient Network-on-Chip Router for Dataflow architecture

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Journal of computer Science & technology 2017年第1期32卷 11-25页

作者： Xiao-Wei Shen Xiao-Chun Ye Xu Tan Da Wang Lunkai Zhang Wen-Ming Li Zhi-Min Zhang Dong-Rui Fan Ning-Hui Sun State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 100049 China Department of Computer Science The University of Chicago IL 60637 U.S.A.

Dataflow architecture has shown its advantages in many high-performance computing cases. In dataflow computing, a large amount of data are frequently transferred among processing elements through the network-on-chip （NoC）. Thus the router design has a significant impact on the performance of dataflow architecture. Common routers are designed for control-flow multi-core architecture and we find they are not suitable for dataflow architecture. In this work, we analyze and extract the features of data transfers in NoCs of dataflow architecture： multiple destinations, high injection rate, and performance sensitive to delay. Based on the three features, we propose a novel and efficient NoC router for dataflow architecture. The proposed router supports multi-destination; thus it can transfer data with multiple destinations in a single transfer. Moreover, the router adopts output buffer to maximize throughput and adopts non-flit packets to minimize transfer delay. Experimental results show that the proposed router can improve the performance of dataflow architecture by 3.6x over a state-of-the-art router.

关键词： multi-destination router network-on-chip dataflow architecture high-performance computing

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Correction to: Gyral-sulcal contrast in intrinsic functional brain networks across task performances

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Brain imaging and behavior 2021年第4期15卷 2235页

作者： Lin Zhao Tuo Zhang Lei Guo Tianming Liu Xi Jiang School of Automation Northwestern Polytechnical University Xi'an China. Cortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center The University of Georgia Athens GA USA. School of Automation Northwestern Polytechnical University Xi'an China. tuozhang@***. School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China. xijiang@***.

A Correction to this paper has been published: https://***/10.1007/s11682-020-00426-z

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Reference study of CityGML software support: The GeoBIM benchmark 2019 — Part II

arXiv

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arXiv 2020年

作者： Noardo, Francesca Ohori, Ken Arroyo Biljecki, Filip Ellul, Claire Harrie, Lars Krijnen, Thomas Eriksson, Helen van Liempt, Jordi Pla, Maria Ruiz, Antonio Hintz, Dean Krueger, Nina Leoni, Cristina Leoz, Leire Moraru, Diana Vitalis, Stelios Willkomm, Philipp Stoter, Jantien 3D Geoinformation Delft University of Technology Delft Netherlands Department of Architecture Department of Real Estate National University of Singapore Singapore Department of Civil Environmental and Geomatic Engineering University College London London United Kingdom Department of Physical Geography and Ecosystem Science Lund University Sweden Institut Cartogràfic i Geològic de Catalunya Spain Safe Software Surrey Canada M.O.S.S. Computer Grafik Systeme GmbH Taufkirchen Germany Department of Civil Constructional and Environmental Engineering Sapienza University of Rome Rome Italy Tracasa Pamplona Spain Ordnance Survey United Kingdom

OGC CityGML is an open standard for 3D city models intended to foster interoperability and support various applications. However, through our practical experience and discussions with practitioners, we have noticed several problems related to the implementation of the standard and the use of standardized data. Nevertheless, a systematic investigation of these issues has never been performed, and there is thus insufficient evidence that can be used for tackling the problems. The GeoBIM benchmark project is aimed at finding such evidence by involving external volunteers, reporting on tools behaviour about relevant aspects (geometry, semantics, georeferencing, functionalities), analysed and described in this paper. This study explicitly pointed out the critical points embedded in the format as an evidence base for future development. This paper is in tandem with Part I, describing the results of the benchmark related to IFC, counterpart of CityGML within building information modelling. Copyright © 2020, The Authors. All rights reserved.

关键词： Interoperability

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A new direction to promote the implementation of artificial intelligence in natural clinical settings

arXiv

引用

arXiv 2019年

作者： Huang, Yunyou Zhang, Zhifei Wang, Nana Li, Nengquan Du, Mengjia Hao, Tianshu Zhan, Jianfeng State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Department of Physiology and Pathophysiology Capital Medical University Beijing China Shenzhen University Shenzhen Guangdong China

Artificial intelligence (AI) researchers claim that they have made great 'achievements' in clinical realms. However, clinicians point out the so-called 'achievements' have no ability to implement into natural clinical settings. The root cause for this huge gap is that many essential features of natural clinical tasks are overlooked by AI system developers without medical background. In this paper, we propose that the clinical benchmark suite is a novel and promising direction to capture the essential features of the real-world clinical tasks, hence qualifies itself for guiding the development of AI systems, promoting the implementation of AI in real-world clinical practice. Copyright © 2019, The Authors. All rights reserved.

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Eager to Learn vs. Quick to Complain? How a socially adaptive robot architecture performs with different robot personalities

Eager to Learn vs. Quick to Complain? How a socially adaptiv...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ana Tanevska Francesco Rea Giulio Sandini Lola Cañamero Alessandra Sciutti Department of Robotics Brain and Cognitive Science Italian Institute of Technology (IIT) Genova Italy Embodied Emotion Cognition and (Inter-)Action (EECAiA) Lab School of Computer Science University of Hertfordshire Hatfield United Kingdom Cognitive Architecture for Collaborative Technologies Unit Italian Institute of Technology (IIT) Genova Italy

A social robot that is aware of our needs and continuously adapts its behaviour to them has the potential of creating a complex, personalized, human-like interaction of the kind we are used to have with our peers in our everyday lives. We are interested in exploring how would an adaptive architecture function and personalize to different users when given different initial values of its variables, i.e. when implementing the same adaptive framework with different robot personalities. Would an architecture that learns very quickly outperform a slower but steadier learning profile? To further explore this, we propose a cognitive architecture for the humanoid robot iCub supporting adaptability and we attempt to validate its functionality and test different robot profiles.

关键词： Robots computer architecture Face Testing Skin Torso Visualization

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