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11th International Conference on Key engineering Materials, ICKEM 2021

作者： Nikoloutsopoulos, Nikolaos D. Pandermarakis, Zacharias G. Papadioti, Aikaterini Douvis, Panagiotis J/V Ellisdon S.A. – Technerga Α.Τ.Ε.Ε Kastamonis 118 Nea Ionia142 35 Greece Region of Attica Directorate of Environment and Climate Change Polytechniou 4 Athens104 33 Greece School of Architecture Computing and Engineering University of East London UK – AKMI Metropolitan Campus Akadimias 42 Athens106 72 Greece Sika Hellas A.B.E.E. Protomagias 15 Kryoneri145 68 Greece

ISBN: (纸本)9783035738872

In this study we investigate the addition of short polypropylene (PP) fibers in cement mortars for a wide volume percentage range. These fibers are dispersed easily in fresh mortar and create a dense network, whereas have as result the cracking reduction during dry shrinkage and the improvement of post peak response. A modified superplasticizer by lignosulfonate polymers basis was used, that keeps at low level the water to cement ratio and thus resulting to an improved mortar’s workability. Compressive strength, three-point flexural strength, drying shrinkage of hardened mortar, flow table test and air content of fresh mortar were studied in a range of volume percentages. The experimental response according to volume percentage was approximated by suitably attached theoretical models. The comparison of the obtained experimental values was done with unreinforced specimens as reference samples. From results elaboration it is concluded that the addition of PP fibers in cementitious mortars improves mortars post-peak response but weaken their compressive and flexural strengths and worsen their workability. © 2021 Trans Tech Publications Ltd, Switzerland.

关键词： Mortar

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UNDERSTANDING THE INTERACTION BETWEEN VIRTUAL DESIGN, CONSTRUCTION AND LEAN CONSTRUCTION 29

UNDERSTANDING THE INTERACTION BETWEEN VIRTUAL DESIGN, CONSTR...

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29th Annual Conference of the International Group for Lean Construction, IGLC 2021

作者： Rodriguez, Maria Guadalupe Mandujano Cardenas, Luis Fernando Alarcon Dave, Bhargav A. Mourgues, Claudio Koskela, Lauri MARO Consulting Huejutla de Reyes Hidalgo Mexico Dept. of Construction Engineering and Management Pontifica Universidad Católica de Chile Escuela de Ingeniería Casilla 360 Correo 22 Santiago de Chile Chile Dept. of Computing Aalto Univ. Espoo02150 Finland School of Art Design and Architecture Univ. of Huddersfield Huddersfield HD1 3DH United Kingdom

ISBN: (纸本)9786124802546

There have been important advances regarding the synergies between Building Information Modeling (BIM) - as part of Virtual Design and Construction (VDC) - and Lean Construction. However, the literature does not fully explore the nature of these synergies nor the conceptual reasons behind them. This better understanding of these synergies would allow the architecture, engineering and Construction (AEC) industry to achieve better Lean and VDC implementations and would provide a stepping-stone for the academia to continue building on these synergies. This article presents a thorough literature review based on leading international journals, conference proceedings and books, to explore the synergies between Lean Construction and VDC, including BIM (product), process and organization modeling. As part of this review, the article tests mechanisms about interaction mechanisms, previously mentioned in the literature. The findings indicate that using the entire VDC framework, the positive interactions between Lean and VDC increased significantly with respect to the same analysis restricted to the interaction between Lean and BIM. Identifying these new interactions and interaction mechanisms can help the AEC industry take a more holistic approach and generate improvements in every project phase. © Prof. Luis F. Alarcón and Assoc. Prof. Vicente González, IGL2021 All rights reserved.

关键词： Architectural design

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Motor adaptation and internal model formation in a robot-mediated forcefield

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Psychoradiology 2021年第2期1卷 73-87页

作者： Myriam Taga Annacarmen Curci Sara Pizzamigglio Irene Lacal Duncan L.Turner Cynthia H.Y.Fu 无 School of Health Sports and BioscienceUniversity of East LondonLondonUK Department of Computer Science School of ArchitectureComputing and EngineeringUniversity of East LondonLondonUK Department of Physiology and Pharmacology Sapienza UniversityRomeItaly School of Psychology University of East LondonLondonUK Centre for Affective Disorders Institute of PsychiatryPsychology and NeuroscienceKing’s College LondonLondonUK

Background:Motor adaptation relies on error-based learning for accurate movements in changing ***,the neurophysiological mechanisms driving individual differences in performance are *** magnetic stimulation(TMS)-evoked potential can provide a direct measure of cortical ***:To investigate cortical excitability as a predictor of motor learning and motor adaptation in a robot-mediated ***:A group of 15 right-handed healthy participants(mean age 23 years)performed a robot-mediated forcefield perturbation *** were two conditions:unperturbed non-adaptation and perturbed *** was applied in the resting state at baseline and following motor adaptation over the contralateral primary motor cortex(left M1).Electroencephalographic(EEG)activity was continuously recorded,and cortical excitability was measured by TMS-evoked potential(TEP).Motor learning was quantified by the motor learning ***:Larger error-related negativity(ERN)in fronto-central regions was associated with improved motor per-formance as measured by a reduction in trajectory *** TEP N100 peak amplitude predicted motor learning(P=0.005),which was significantly attenuated relative to baseline(P=0.0018)following motor ***:ERN reflected the formation of a predictive internal model adapted to the forcefield *** in TEP N100 amplitude reflected an increase in cortical excitability with motor adaptation reflecting neuroplastic changes in the sensorimotor *** N100 is a potential biomarker for predicting the outcome in robot-mediated therapy and a mechanism to investigate psychomotor abnormalities in depression.

关键词： EEG TMS motor adaptation robot-mediated forcefield N100 ERN

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MAPA: Multi-Accelerator Pattern Allocation Policy for Multi-Tenant GPU Servers

MAPA: Multi-Accelerator Pattern Allocation Policy for Multi-...

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Supercomputing Conference

作者： Kiran Ranganath Joshua D. Suetterlein Joseph B. Manzano Shuaiwen Leon Song Daniel Wong Department of Electrical and Computer Engineering University of California Riverside CA USA High-Performance Computing Group Pacific Northwest National Lab WA USA Future System Architecture Lab School of Computer Science University of Sydney Sydney Australia

ISBN: (数字)9781450384421

ISBN: (纸本)9781665483902

Multi-accelerator servers are increasingly being deployed in shared multi-tenant environments (such as in cloud data centers) in order to meet the demands of large-scale compute-intensive workloads. In addition, these accelerators are increasingly being inter-connected in complex topologies and workloads are exhibiting a wider variety of inter-accelerator communication patterns. However, existing allocation policies are ill-suited for these emerging use-cases. Specifically, this work identifies that multi-accelerator workloads are commonly fragmented leading to reduced bandwidth and increased latency for inter-accelerator communication. We propose Multi-Accelerator Pattern Allocation (MAPA), a graph pattern mining approach towards providing generalized allocation support for allocating multi-accelerator workloads on multi-accelerator servers. We demonstrate that MAPA is able to improve the execution time of multi-accelerator workloads and that MAPA is able to provide generalized benefits across various accelerator topologies. Finally, we demonstrate a speedup of 12.4% for 75th percentile of jobs with the worst case execution time reduced by up to 35% against baseline policy using MAPA.

关键词： Network topology Processor scheduling High performance computing Graphics processing units Throughput Hardware Topology

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Unleashing the Low-Precision Computation Potential of Tensor Cores on GPUs

Unleashing the Low-Precision Computation Potential of Tensor...

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International Symposium on Code Generation and Optimization (CGO)

作者： Guangli Li Jingling Xue Lei Liu Xueying Wang Xiu Ma Xiao Dong Jiansong Li Xiaobing Feng School of Computer Science and Technology University of Chinese Academy of Sciences China School of Computer Science and Engineering University of New South Wales Australia SKL of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China College of Computer Science and Technology Jilin University China

ISBN: (数字)9781728186139

ISBN: (纸本)9781728186146

Tensor-specialized hardware for supporting low-precision arithmetic has become an inevitable trend due to the ever-increasing demand on computational capability and energy efficiency in intelligent applications. The main challenge faced when accelerating a tensor program on tensor-specialized hardware is how to achieve the best performance possible in reduced precision by fully utilizing its computational resources while keeping the precision loss in a controlled manner. In this paper, we address this challenge by proposing QUANTENSOR, a new approach for accelerating general-purpose tensor programs by replacing its tensor computations with low-precision quantized tensor computations on NVIDIA Tensor Cores. The key novelty is a new residual-based precision refinement technique for controlling the quantization errors, allowing tradeoffs between performance and precision to be made. Evaluation with GEMM, deep neural networks, and linear algebra applications shows that QUANTENSOR can achieve remarkable performance improvements while reducing the precision loss incurred significantly at acceptable overheads.

关键词： Tensors Quantization (signal) Neural networks Market research Hardware Acceleration Optimization

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An Ultra-Low Power 3-T Chaotic Map based True Random Number Generator

An Ultra-Low Power 3-T Chaotic Map based True Random Number ...

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IEEE Asian Hardware-Oriented Security and Trust (AsianHOST)

作者： Lijuan Han Yuan Cao Lei Qian Haodong Xie Chip-Hong Chang College of Internet of Tings Engineering Hohai University Chang Zhou China Changzhou Galaxy Century Microelectronics Co. Ltd. State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences School of Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781665441865

In this paper, discrete-time chaos generator is exploited for lightweight and energy-efficient true random number generator (TRNG) implementation. The chaos generator is realized with a two-stage tent map circuit with feedback. Each stage consists of three transistors. Its transient characteristics can be tuned over a range of bias voltage to realize a family of tent map functions. The chaotic output voltage amplitude of each stage is highly sensitive to the environmental noise. The difference signal between two such chaos generators at each stage is amplified to produce a random binary output. The output of the quantized sense amplifier is sampled at twice the bit rate of each stage of tent map circuit. The proposed design was simulated using a standard 55 nm 1.2 V CMOS process. The results show that it has a very low power consumption of 10.98 μW. It has an ultra-low energy consumption of only 5.49 pJ/bit at a throughput of 2 Mbps, which is 19x lower than the recently reported state-of-the-art and the most power efficient chaotic TRNGs. The random bit stream generated by the proposed TRNG has passed entropy, ACF and NIST randomness tests.

关键词： Chaos Voltage NIST Throughput CMOS process Generators Entropy

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Semantic process mining: A conceptual application of main tools, framework and model analysis

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International Journal of Hybrid Intelligent Systems 2020年第3期16卷 127-147页

作者： Okoye, Kingsley Writing Lab TecLabs Vicerrectoría de Investigación y Transferencia de Tecnología Tecnologico de Monterrey CP Nuevo Leon Monterrey 64849 Mexico School of Architecture Computing and Engineering College of Arts Technologies and Innovation University of East London E16 2RD United Kingdom

Semantics has been a major challenge when applying the process mining (PM) technique to real-time business processes. The several theoretical and practical efforts to bridge the semantic gap has spanned the advanced notion of the semantic-based process mining (SPM). Fundamentally, the SPM devotes its methods to the idea of making use of existing (semantic) technologies to support the analysis of PM techniques. In principle, the semantic-based process mining method is applied through the acquisition and representation of abstract knowledge about the domain processes in question. To this effect, this paper demonstrates how the semantic concepts and process modelling (reasoning) methods are used to improve the outcomes of PM techniques from the syntactic to a more conceptual level. To do this, the study proposes an SPM-based framework that shows to be intelligent with a high level of semantic reasoning aptitudes. Technically, this paper introduces a process mining approach that uses information (semantics) about different activities that can be found in any given process to make inferences and generate rules or patterns through the method for annotation, semantic reasoning, and conceptual assertions. In turn, the method is theoretically applied to enrich the informative values of the resultant models. Also, the study conducts and systematically reviews the current tools and methods that are used to support the outcomes of the process mining as well as evaluates the results of the different methods to determine the levels of impact and its implications for process mining. © 2020 - IOS Press and the authors. All rights reserved.

关键词： annotation events log ontologies process mining process models Semantic modelling semantic reasoning

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Implications of circular strategies on energy, water, and GHG emissions in informal housing in Lima

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Energy and Buildings 2025年 344卷

作者： Sarmiento-Pastor, Jaime Lira-Chirif, Andrés Rondinel-Oviedo, Daniel R. Keena, Naomi Dyson, Anna Raugei, Marco Acevedo-De-los-Ríos, Alejandra Scientific Research Institute University of Lima Lima Peru Peter Guo-Hua Fu School of Architecture Faculty of Engineering McGill University Montreal Canada Yale Center for Ecosystems + Architecture 180 York Street New Haven 06511 CT United States School of Engineering Computing and Mathematics Oxford Brookes University United Kingdom Center for Life Cycle Analysis Columbia University NY United States Louvain Research Institute for Landscape Architecture and Built Environment (LAB) University of Louvain Louvain-la-Neuve Belgium

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Cloud-based remote control framework for unmanned surface vehicles ⁎

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IFAC-PapersOnLine 2020年第2期53卷 14564-14569页

作者： Zhao Wang Shaolong Yang Xianbo Xiang Antonio Vasilijević Nikola Mišković Ðula Nađ School of Naval Architecture and Ocean Engineering Huazhong University of Science and Technology Wuhan 430074 China Hubei Key Laboratory of Naval Architecture and Ocean Engineering Hydrodynamics (HUST) Wuhan 430074 PR China Laboratory for Underwater Systems and Technologies Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

This paper proposes a cloud-based mission control framework for a fleet of unmanned vehicles. The framework enables easy remote access to fleet operations regardless of operator location. By leveraging cloud-based technologies the framework accomplishes scalable monitoring, remote control, data acquisition and sharing. While the front-end is applicable across mobile robotic systems, the back-end presented in this paper provides integration with the Robot Operating System (ROS); thus, enabling integration of various marine robotic agents based on the same robot framework. The proposed framework operation is demonstrated on the H2OmniX unmanned surface vehicles during trials in Biograd na Moru, Croatia.

关键词： remote control distributed control cloud-based control Robot Operating System

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Predicting the Governing Factors for the Release of Colloidal Phosphorus Using Machine Learning

SSRN

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SSRN 2024年

作者： Khan, Sangar Gao, Huimin Milham, Paul J. Eltohamy, Kamel Mohamed Ullah, Habib Mu, Hongli Gao, Meixiang Yang, Xiaodong Hamid, Yasir Hooda, Peter S. Shaheen, Sabry M. Wu, Naicheng Department of Geography and Spatial Information Techniques Ningbo University Ningbo315211 China Hawkesbury Institute for the Environment University of Western Sydney LB 1797 PenrithNSW2751 Australia Water Relations and Field Irrigation Department Agricultural and Biological Research Division National Research Centre Cairo12622 Egypt College of Environmental Resource Sciences Zhejiang University Hangzhou310058 China Innovation Center of Yangtze River Delta Zhejiang University Zhejiang311400 China Faculty of Engineering Computing and the Environment Kingston University London United Kingdom University of Wuppertal School of Architecture and Civil Engineering Laboratory of Soil Groundwater Management Pauluskirchstraße 7 Wuppertal42285 Germany

The use of machine learning models in predicting the important variable for colloidal-phosphorus (P) release from soils is a relatively new area of research. Therefore, in this study, we investigated the major determinants of colloidal-P release from different land use/types such as farmland, desert, and forest soils and rivers. The study utilizes the structural equation model (SEM), multiple linear regression (MLR), and three learning models (Random Forest (RF), Support Vector Regression (SVR), and Shapley Additive exPlanations eXtreme Gradient Boosting (SHAP XGBoost)) to predict the release of colloidal-P from different soils by using soil iron (Fe), aluminum (Al), calcium (Ca), pH, total organic carbon (TOC) and precipitation as independent variables. Results show that colloidal-cations (Fe, Al, Ca) and colloidal-TOC strongly influence colloidal-P release, with bioclimatic variables and pH having weaker effects. The SHAP Xgboost model outperforms the other models, with an R2 value of 0.94 and an RMSE of 0.09. The relative importance ranking of the variables for predicting the release of colloidal-P from soils to water is consistent across all three models, with colloidal TOC ranked as the most important factor followed by colloidal-Ca, colloidal-Al, and precipitation. Partial dependence plot analysis demonstrates that increasing colloidal TOC leads to increased soil colloidal-P release. According to our research, the SHAP XGBoost model provides significant information that can help determine the variables that considerably influence CP contents as compared to RF, SVM, and MLR. © 2024, The Authors. All rights reserved.

关键词： Soils

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