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Deformation mechanism and collapse treatment of the rock surrounding a shallow tunnel based on on-site monitoring

Journal of Mountain science 2020年第12期17卷 2897-2914页

作者： QIU Hong-zhi CHEN Xiao-qing WU Qi-hong WANG Ren-chao ZHAO Wan-yu QIAN Ke-jiang School of Architecture and Civil Engineering Chengdu UniversityChengdu 610106China Key Laboratory of Mountain Hazards and Earth Surface Processes Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China Hunan International Scientific and Technological Innovation Cooperation Base of Advanced Construction and Maintenance Technology of Highway Changsha University of Science&TechnologyChangsha 410114China School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

When tunnels are constructed at shallow depths in areas with poor geological conditions,such as portal sections,valleys and hillsides in regions with granitic bedrock,considerable excavation-induced deformation of the surrounding rock may occur,potentially resulting in tunnel *** main reason for these problems is the lack of understanding of the deformation mechanism and evolution of the soft granitic rock surrounding the tunnel and the adoption of inappropriate construction technology and *** article analyzes the deformation mechanism of the rock surrounding a shallow tunnel based on in situ monitoring data as a case study and suggests that certain measures should be taken to effectively control the deformation of the surrounding rock and to minimize the potential for tunnel *** results show that the deformation of the granitic soil surrounding the tunnel can be divided into three stages:the rapid deformation stage,the slow deformation stage and the stabilization *** construction methods should be carefully selected to ensure safety during tunnel excavation in the first *** avoid secondary disasters caused by tunnel collapses,three treatment measures may be implemented as part of safety management:enhancing the monitoring of the surrounding rock deformation,adjusting the construction methods and optimizing the support *** particular,accurate monitoring data and timely information feedback play a vital role in tunnel ***,engineers with considerable engineering experience and professional knowledge are needed to analyze the monitoring data and make accurate predictions of tunnel deformation to ensure that reasonable measures are taken in the process of shallow tunnel excavation.

关键词： Shallow tunnel Surrounding rock deformation Field monitoring Treatment for collapse Information feedback

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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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A small-footprint accelerator for large-scale neural networks

A small-footprint accelerator for large-scale neural network...

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作者： Chen, Tianshi Zhang, Shijin Liu, Shaoli Du, Zidong Luo, Tao Gao, Yuan Liu, Junjie Wang, Dongsheng Wu, Chengyong Sun, Ninghui Chen, Yunji Temam, Olivier State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China TNLIST Tsinghua University Beijing100084 China Inria Saclay France CAS Center for Excellence in Brain Science China

Machine-learning tasks are becoming pervasive in a broad range of domains, and in a broad range of systems (from embedded systems to data centers). At the same time, a small set of machine-learning algorithms (especially Convolutional and Deep Neural Networks, i.e., CNNs and DNNs) are proving to be state-of-theart across many applications. As architectures evolve toward heterogeneous multicores composed of a mix of cores and accelerators, a machine-learning accelerator can achieve the rare combination of efficiency (due to the small number of target algorithms) and broad application scope. Until now, most machine-learning accelerator designs have been focusing on efficiently implementing the computational part of the algorithms. However, recent state-of-the-art CNNs and DNNs are characterized by their large size. In this study, we design an accelerator for large-scale CNNs and DNNs, with a special emphasis on the impact of memory on accelerator design, performance, and energy. We show that it is possible to design an accelerator with a high throughput, capable of performing 452 GOP/s (key NN operations such as synaptic weight multiplications and neurons outputs additions) in a small footprint of 3.02mm2 and 485mW;compared to a 128-bit 2GHz SIMD processor, the accelerator is 117.87?faster, and it can reduce the total energy by 21.08×. The accelerator characteristics are obtained after layout at 65nm. Such a high throughput in a small footprint can open up the usage of state-of-the-art machine-learning algorithms in a broad set of systems and for a broad set of applications. © 2015 ACM.

关键词： Deep neural networks

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Robotic additive construction of bar structures: unified sequence and motion planning

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Construction Robotics 2021年第2期5卷 115-130页

作者： Huang, Yijiang Garrett, Caelan R. Ting, Ian Parascho, Stefana Mueller, Caitlin T. Building Technology Program Department of Architecture Massachusetts Institute of Technology Cambridge USA Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge USA CREATE Laboratory School of Architecture Princeton University Princeton USA

Additive robotic construction of building-scale discrete bar structures, such as trusses and space frames, is increasingly attractive due to the potential improvements in efficiency, safety, and design possibilities. However, programming complex robots, such as manipulators with seven degrees of freedom, to successfully complete construction tasks can be tedious, challenging, or impossible for a human to do manually. Namely, the structure must be constructed in a sequence that preserves structural properties, such as stiffness, at each step. At the same time, this sequence must allow for the robot to precisely manipulate elements within the in-progress structure while respecting geometric constraints that, for example, ensure the robot does not collide with what it has built. In this work, we present an automated and newly generalized planning approach for jointly finding a construction sequence and robot motion plan for additive construction that satisfies these requirements. Our approach can be applied in a variety of additive construction processes, and we demonstrate it specifically on spatial extrusion and discrete bar assembly in this paper. We demonstrate the effectiveness of our approach on several simulated and real-world extrusion and assembly tasks, including a human-scale physical prototype, for which our algorithm is deployed for the first time to plan the assembly of a complicated double tangent bar system design.

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Research on answer extraction method for domain question answering system(QA)

Research on answer extraction method for domain question ans...

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2009 International Conference on Computational Intelligence and Security, CIS 2009

作者： Mao, Cun-Li Li, Li-Na Yu, Zheng-Tao Han, Lu Guo, Jian-Yi Lei, Xiong-Li School of Information Engineering and Automation Kunming University of Science and Technology Kunming 650051 China Institute of Intelligent Information Processing Computer Technology Application Key Laboratory of Yunnan Province Kunming 650051 China School of Computer Science and Technology Kunming College of Metallurgy Kunming 650093 China School of Architecture and Arts Kunming College of Metallurgy Kunming 650093 China

ISBN: (纸本)9780769539317

The domain knowledge has a direct impact on the result of question - answering (Q & A) in the restricted domain Question Answering System (QA). In this paper, a method of answer extraction for domain Chinese question-and-answer (Q&A) is proposed, which based on the analysis of interrogative sentence and the answer type, carrying on the text retrieval with the help of the domain knowledge and obtaining the relevant paragraphs of the question as the candidate answer. For the question of numeral or list entity type, extracted the question center related domain entity as the answers by adopting the naming entity recognition. For the definition questions, the sentences or paragraphs with higher relevance can be extracted to become the answer based on the relevance ranking between the candidate sentences or paragraphs and questions by combined the computing method of keywords weighting and the method of semantic similarity between the sentences and questions. Experimented on the answer extraction in Yunnan tourism domain, the results show that more remarkable effects have been achieved by adopting the method of answer extraction from domain Chinese question-and-answer. © 2009 IEEE.

关键词： Domain Knowledge

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Practical Stabilization of Passive Nonlinear Systems with Limited Control

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IFAC-PapersOnLine 2019年第16期52卷 460-465页

作者： B. Jayawardhana M.Z. Almuzakki A. Tanwani Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen The Netherlands Department of Computer Science Faculty of Science and Computer Universitas Pertamina Jakarta Indonesia Laboratory for Analyses and Architecture of Systems (LAAS) –CNRS Université de Toulouse France

This article addresses output feedback stabilization of continuous-time nonlinear systems by choosing control actions from a finite set. Working under the assumption that the system under consideration is passive and large-time norm observable, we propose a static feedback mapping, from the output space to the finite set of control actions, which is shown to be practically stabilizing if the convex hull of certain control actions (in the chosen finite set) contains the origin in its interior. Consequently, to construct this stabilizing feedback, it suffices to have, in addition to a zero symbol, another m + 1 elements in the control set which form an m -simplex in ℝ m (the input, and output space).

关键词： Nonlinear passive systems finite control set output feedback binary control

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Energy-Efficient and Reliable Federated Learning in Heterogeneous Mobile-Edge Computing

Energy-Efficient and Reliable Federated Learning in Heteroge...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Yan Xu Liying Li Peijin Cong Junlong Zhou School of Computer Science and Engineering Nanjing University of Science and Technology China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China

As a decentralized machine learning paradigm, Federated Learning (FL) is an emerging technique to protect user data privacy in Mobile Edge Computing (MEC). FL adopts the idea of distributed privacy computing, enabling the terminal devices to train machine learning models required by servers locally and upload model parameters to servers for aggregation. However, in the process of coupling FL with MEC systems, device heterogeneity, malicious use of poisoned data by users and limited system resources will seriously affect FL training accuracy, system reliability and energy efficiency. In this paper, a highly reliable and energy-efficient FL scheme is designed to solve these issues. Specifically, we first propose a calculation method for estimating the reliability of heterogeneous devices. Then, we design a highly reliable device selection scheme based on devices’ reliability, computing power, and participation times. Finally, we utilize the slack time in FL training to dynamically adjust the voltage and frequency of devices for reducing the energy consumption of training. Experimental results show that our proposed scheme improves the accuracy by up to 36.45% on average and saves energy by up to 48.63% when compared to the baseline and benchmarking methods.

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Round-robin based scheduling algorithms for FIFO IQ switch

Round-robin based scheduling algorithms for FIFO IQ switch

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IEEE International Conference on Networking, Sensing and Control

作者： Xiao-jing Zhu Hong-bo Zeng Kun Huang Ge Zhang Department of Computer Science and Technology University of Science and Technology China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy and Sciences Beijing China

Network on chip (NoC) has become an active research area for high performance computer. Based on round-robin scheduling algorithm, we present three new scheduling algorithms for FIFO input queue (IQ) switches of network on chip, which are called rr-path, rr-dist and rr-al respectively, rr-path schedules the NoC traffic according to the distance between the source node and the destination node, and rr-dist schedules the NoC traffic according to the distance between the current and the destination nodes, and rr-al schedules the NoC traffic according to the difference between the arrival and the left flits numbers of every ports. We implement these algorithms in a network simulator, and analyze their performance using hotspot and uniform traffic patterns. Compared to round-robin scheduling algorithm, all of the new algorithms can reduce the max communication latency. In most cases, they can also reduce the average communication latency. Consequently, these new algorithms can improve the performance of multiprocessor systems.

关键词： Scheduling algorithm Network-on-a-chip Telecommunication traffic Traffic control Switches Round robin Processor scheduling Delay computer networks High performance computing

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Caira - A Creative Artificially-Intuitive and Reasoning Agent as conductor of telematic music improvisations

Caira - A Creative Artificially-Intuitive and Reasoning Agen...

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131st Audio Engineering Society Convention 2011

作者： Braasch, Jonas Bringsjord, Selmer Kuebler, Colin Oliveros, Pauline Parks, Anthony Van Nort, Doug Graduate Program in Architectural Acoustics Rensselaer Polytechnic Institute School of Architecture Troy NY 12180 United States Laboratory Department of Cognitive Science Rensselaer Polytechnic Institute Troy NY 12180 United States Laboratory Department of Computer Science Rensselaer Polytechnic Institute Troy NY 12180 United States Arts Department Rensselaer Polytechnic Institute Troy NY 12180 United States

ISBN: (纸本)9781618393968

This paper reports on the architecture and performance of the Creative Artificially-Intuitive and Reasoning Agent Caira as a conductor for improvised avant-garde music. Caira's listening skills are based on a music recognition system that simulates the human auditory periphery to perform an Auditory Scene Analysis (ASA). Its simulation of cognitive processes includes a comprehensive cognitive calculus for reasoning and decision-making using logic-based reasoning. Caira is used as conductor for live music performances with distributed ensembles, where the musicians are connected via the internet. Caira uses a visual score and directs the ensemble members based on tension arc estimations for the individual music performers.

关键词： Decision making

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Reducing Redundancy in Data Organization and Arithmetic Calculation for Stencil Computations

Reducing Redundancy in Data Organization and Arithmetic Calc...

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Supercomputing Conference

作者： Kun Li Liang Yuan Yunquan Zhang Yue Yue State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Scienceslice Beijing China

ISBN: (数字)9781450384421

ISBN: (纸本)9781665483902

Stencil computation is one of the most important kernels in various scientific and engineering applications. A variety of work has focused on vectorization techniques, aiming at exploiting the in-core data parallelism. However, they either incur spatial data conflicts or hurt the data locality when integrated with tiling. In this paper, a novel spatial computation folding is devised to reduce the data reorganization overhead for vectorization and preserve the data locality for tiling in the data space simultaneously. We then propose an approach of temporal computation folding enhanced with shifts reusing, tessellate tiling, and semi-automatic code generation. It aims to further reduce the redundancy of arithmetic calculations and exploit the register reuse along the time dimension. Experimental results on the AVX2 and AVX-512 CPUs show that our approach obtains significant performance improvements compared with state-of-the-art techniques.

关键词： Codes High performance computing Redundancy Organizations Parallel processing Spatial databases Computational efficiency

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