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Fire Science and Fire Protection engineering (ICFSFPE), Conference on

作者： Jinlu Sun Shouxiang Lu Jiansheng Wu Ting Sun Kai Shi Shenshi Huang School of Urban Planning and Design Peking University Shenzhen Graduate School Shenzhen China Skate Key Laboratory of Fire Science University of Science and Technology of China Hefei China The Postdoctoral Innovation Base Smart City Research Institute of China Electronics Technology Group Corporation Shenzhen China Smart City Research Institute of China Electronics Technology Group Corporation Shenzhen China Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Science Shenzhen China

ISBN: (数字)9781728153223

ISBN: (纸本)9781728153230

Ship listing and motion affects individual movement pattern on board, thus individual walking behavior would be significantly different from those on level ground. To quantify the correlation between individual walking speed and gait parameters of individuals on board, we designed a ship corridor simulator, where we performed both fast and freely walking experiments considering the effect of ship heeling and trim. Results indicated that both step length and step frequency are positively linearly associated with individual walking speed with different degrees, with one exception that individuals could adopt quick and tiny steps in a much lower walking speed with even larger step frequency to keep balance when the trim-up or trim-down angle exceeds 20°. However, there is no direct relationship that could be observed between step width and individual walking speed, despite that walking with wider steps might weaken individual stability and increase fall risk. Moreover, though individual experimental subjects tend to walk along the right side due to cultural factors, the walking routes are more likely to be close to the handrail arranged on the opposite side for safety purpose when the trim-down angle exceeds 20° even though some of them did not use the handrail actually. This work would be a primary consideration in the development of evacuation models and the design of evacuation facilities on board.

关键词： Legged locomotion Marine vehicles Spatiotemporal phenomena Frequency measurement Foot Stability analysis Length measurement

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The Influences NaOH Treatment on Polypropylene/Cyperus Odoratus (PP/CY) Composites: Tensile and Morphology 1

The Influences NaOH Treatment on Polypropylene/<i>Cyperus Od...

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1st International Conference on Green and Sustainable computing (ICoGeS)

作者： Dahham, Omar S. Noriman, N. Z. Hamzah, R. Al-Samarrai, Marwa N. Idrus, S. Z. Syed Shayfull, Z. Adam, T. Mohammed, M. Center of Excellence Geopolymer and Green Technology (CEGeoGTech) Faculty of Engineering Technology (FETech) Universiti Malaysia Perlis (UniMAP) UniCITI Alam Campus Sungai Chucuh Padang Besar Perlis 02100 Malaysia School of Human Development and Techno-communication (IKOM) Green Advanced Computing and Technology (GREAT) Research Group-CEGeoGTech Universiti Malaysia Perlis (UniMAP) Malaysia School of Manufacturing Engineering Universiti Malaysia Perlis Arau 02600 Malaysia Green Design and Manufacture Research Group Center of Excellence Geopolymer and Green Technology (CEGeoGTech) Universiti Malaysia Perlis Kangar 0100 Malaysia Institute of Nano Electronic Engineering (INEE) Universiti Malaysia Perlis (UniMAP) Kangar Perlis 01000 Malaysia Center of Excellence Geopolymer and Green Technology (CEGeoGTech) School of Materials Engineering Universiti Malaysia Perlis (UniMAP) Kompleks Pengajian Jejawi 2 Arau 02600 Malaysia

The bio-plastic composite has attracted the attention of people who work in academic and industrial fields due to the several advantages of this composite as compared with conventional plastic composites. However, the modification of the natural filler used in the bio-composites usually needs a modification before use. In the current work, the chemical modification on Cyperus Odoratus (CY) using different sodium hydroxide (NaOH) concentration at 1, 3, 6 and 9 wt.% were used to investigate the effect of this modification on the tensile properties of Polypropylene/Cyperus Odoratus (PP/CY) composites. The extrusion and injection molding processes were used respectively to prepare the composites. Results suggest that the presence of NaOH, particularly 3 wt.% has improved the tensile strength and the elongation at break of the composite. By contrast, the high NaOH concentration, particularly 9 wt.% has effected negatively on this properties. The tensile modulus increased linearly as NaOH concentration increased in the composites. The SEM micrograph of treated specimens at 3 wt.% NaOH shows improvement on CY surface while 9 wt.% NaOH shows deterioration on the DS surface.

关键词： Sodium hydroxide

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The Effects of SMR L Content on the Properties of ENR-25/RSC Compounds 1

The Effects of SMR L Content on the Properties of ENR-25/RSC...

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1st International Conference on Green and Sustainable computing (ICoGeS)

作者： Dahham, Omar S. Hamzah, R. Noriman, N. Z. Alakrach, A. M. Idrus, S. Z. Syed Shayfull, Z. Adam, T. Mohammed, M. Center of Excellence Geopolymer and Green Technology (CEGeoGTech) Faculty of Engineering Technology (FETech) Universiti Malaysia Perlis (UniMAP) UniCITI Alam Campus Sungai Chucuh Padang Besar Perlis 02100 Malaysia School of Human Development and Techno-communication (IKOM) Green Advanced Computing and Technology (GREAT) Research Group-CEGeoGTech Universiti Malaysia Perlis (UniMAPO) Malaysia School of Manufacturing Engineering Universiti Malaysia Perlis Arau 02600 Malaysia Green Design and Manufacture Research Group Center of Excellence Geopolymer and Green Technology (CEGeoGTech) Universiti Malaysia Perlis Kangar 0100 Malaysia Institute of Nano Electronic Engineering (INEE) Universiti Malaysia Perlis (UniMAP) Kangar Perlis 01000 Malaysia Center of Excellence Geopolymer and Green Technology (CEGeoGTech) School of Materials Engineering Universiti Malaysia Perlis (UniMAP) Kompleks Pengajian Jejawi 2 Arau 02600 Malaysia

Normally, direct introduction of recycled materials into polymer matrix could cause unwanted aggregations, which could effect on the properties of the final product. However, adding third material as a compatibilizer could enhance the properties of the product. This work studied the effects of different SMR L content (2,4,6,8 and 10 Phr) as a compatibilizer on the physical, tensile properties, and cure characteristics of ENR-25/rSC compounds. The results of cure characteristics showed decreasing on scorch time (t(2)) and cure time (t(90)) while increasing on minimum torque (M-L) and maximum torque (M-H) as SMR L increased in ENR25/rSC/SMR L compounds. The values of modulus (M100), tensile strength (Ts), hardness and crosslinking density increased gradually with increasing SMR L while elongation at break (Eb) decreased.

关键词： Tensile strength

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A Smart Context-Aware Program Assistant Based on Dynamic Programming Event Modeling

A Smart Context-Aware Program Assistant Based on Dynamic Pro...

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IEEE International Conference on Software Reliability engineering Workshops (ISSRE Wksp)

作者： Xuejiao Zhao Hongwei Li Yutian Tang Dongjing Gao Lingfeng Bao Ching-Hung Lee NTU School of Computer Science and Engineering Singapore School of Computer Information Engineering Jiangxi Normal University Nanchang China Department of Computing The Hong Kong Polytechnic University Hong Kong School of Computer Science Fudan University Shanghai China College of Computer Science Zhejiang University Hangzhou China Division of Smart Product Design School of Mechanical and Aerospace Engineering Singapore

The following topics are dealt with: program testing; software fault tolerance; program debugging; software reliability; cloud computing; learning (artificial intelligence); program diagnostics; fault diagnosis; softw... 详细信息

ISBN: (纸本)9781538694442

关键词： Web pages Context modeling Monitoring Search engines Browsers Programming

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Auto-contouring FDG-PET/MR images for cervical cancer radiation therapy: An intelligent sequential approach using focally trained, shallow U-Nets

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Intelligence-Based Medicine 2021年 5卷 100026-100026页

作者： Atallah Baydoun Ke Xu Latoya A. Bethell Feifei Zhou Jin Uk Heo Kaifa Zhao Elisha T. Fredman Rodney J. Ellis Pengjiang Qian Raymond F. Muzic Bryan J. Traughber Department of Radiation Oncology University Hospitals Cleveland Medical Center Cleveland OH USA School of Artificial Intelligence and Computer Science Jiangnan University Wuxi Jiangsu 214122 China Jiangsu Key Laboratory of Media Design and Software Technology Jiangnan University Wuxi Jiangsu 214122 China Department of Radiology School of Medicine Case Western Reserve University Cleveland OH 44106 USA Department of Biomedical Engineering Case Western Reserve University Cleveland OH 44106 USA Department of Computing Hong Kong Polytechnic University Hung Hom 999077 Hong Kong Department of Radiation Oncology Penn State Cancer Institute Hershey PA 17033 USA

Background Manual contouring for radiation therapy planning remains the most laborious and time consuming part in the radiation therapy workflow. Particularly for cervical cancer, this task is complicated by the complex female pelvic anatomy and the concomitant dependence on 18 F-labeled Fluorodeoxyglucose (FDG) positron emission tomography (PET) and magnetic resonance (MR) images. Using deep learning, we propose a new auto-contouring method for FDG-PET/MR based cervical cancer radiation therapy by combining the high level anatomical topography and radiological properties, to the low-level pixel wise deep-learning based semantic segmentation. Materials/methods The proposed method: 1) takes advantage of PET data and left/right anatomical symmetry, creating sub-volumes that are centered on the structures to be contoured. 2) Uses a 3D shallow U-Net (sU-Net) model with an encoder depth of 2.3) Applies the successive training of 3 consecutive sU-Nets in a feed forward strategy. 4) Employs, instead of the usual generalized dice loss function (GDL), a patch dice loss function (PDL) that takes into account the Dice similarity index (DSI) at the level of each training patch. Experimental analysis was conducted on a set of 13 PET/MR images was using a leave-one-out strategy. Results Despite the limited data availability, 5 anatomical structures - the gross tumor volume, bladder, anorectum, and bilateral femurs - were accurately (DSI = 0.78), rapidly (1.9 s/structure), and automatically delineated by our algorithm. Overall, PDL achieved a better performance than GDL and DSI was higher for organs at risk (OARs) with solid tissue (e.g. femurs) than for OARs with air-filled soft tissues (e.g. anorectum). Conclusion The presented workflow successfully addresses the challenge of auto-contouring in FDG-PET/MR based cervical cancer. It is expected to expedite the cervical cancer radiation therapy workflow in both, conventional and adaptive radiation therapy settings.

关键词： Cervical cancer Deep learning Image segmentation PET/MR Based radiation therapy U-net

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The soft sensor of the molten steel temperature using the modified maximum entropy based pruned bootstrap feature subsets ensemble method

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Chemical engineering Science 2018年 189卷 401-412页

作者： Xiao-Jun Wang Xiao-Yan Wang Qiang Zhang Zhi-Zhong Mao Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian 116622 China School of Business Administration Dongbei University of Finance and Economics Dalian 116025 China Institute of Automatization College of Information Science and Engineering Northeastern University Shenyang 110004 China

The molten steel temperature in ladle furnace is a significant variable, but it is hard to be measured by real-time detection, which has some bad effects on productions. Soft sensors are alternative and effective techniques to solve this issue. In this paper, the soft sensor of the molten steel temperature established by the Modified Maximum Entropy based Pruned Bootstrap Feature Subsets Ensemble (MMEP-BFSE) method is proposed. Although the Bootstrap Feature Subsets Ensemble (BFSE) temperature model is prominent in the precision and the forecasting speed on the large-scale and noisy data, its main drawback is too many sub-models required to combine, which is not always feasible for applications. To alleviate this drawback, the Modified Maximum Entropy based Pruning (MMEP) approach is presented, in which a subset of sub-models that better approximates the complete ensemble is find based on the maximum Rényi entropy and the trade-off parameter between the precision and the diversity of sub-models. Then, the soft sensor of the temperature based on the MMEP-BFSE is established on the practical data. Experiments show that the proposed soft sensor outperforms the others in the precision, and meets the precision requirements. Sub-models of the BFSE temperature model are substantially pruned with improved generalization by the MMEP approach.

关键词： Chemical process Quality variables Soft sensor Data-driven model Machine learning Ensemble pruning

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African societal challenges transformation through IoT 21

African societal challenges transformation through IoT

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21st Pacific Asia Conference on Information Systems: Societal Transformation Through IS/IT, PACIS 2017

作者： Al-Isma’ili, Salim Li, Mengxiang Shen, Jun He, Qiang Alghazi, Abdulaziz School of Computing and Information Technology University of Wollongong Australia Department of Finance and Design Sciences School of Business Hong Kong Baptist University Hong Kong School of Software and Electrical Engineering Faculty of Science Engineering and Technology Swinburne University of Technology Australia

Very limited trials have been conducted either industrially or academically in trying to uncover the potential of Internet of Things (IoT) in leveraging the societal problems in Africa. Based on the review of the current status of IoT implementation in Africa, we highlighted the potential opportunities to be taken into consideration by different stakeholders to leverage the living standards in the African nations. The study also identified some of the impending challenges that need to be addressed for a successful implementation of IoT solutions. The study proposes a framework that includes the relevant stakeholders, who need to cooperate harmoniously to alleviate the African countries’ challenges in areas such as agriculture and healthcare. This paper also proposes a multi-perspective research framework and aims to test it empirically to understand the views of IoT among users and practitioners in Africa. © PACIS 2017.

关键词： Internet of things

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A multi-view ensemble classification model for clinically actionable genetic mutations

arXiv

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arXiv 2018年

作者： Zhang, Xi Sheryl Chen, Dandi Zhu, Yongjun Che, Chao Su, Chang Zhao, Sendong Min, Xu Wang, Fei Department of Healthcare Policy and Research Weill Cornell Medicine Cornell University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University School of Electronic and Information Engineering Xian Jiaotong University China Research Center for Social Computing and Information Retrieval Harbin Institute of Technology China Department of Computer Science and Engineering Tsinghua University China

This paper presents details of our winning solutions to the task IV of NIPS 2017 Competition Track entitled Classifying Clinically Actionable Genetic Mutations. The machine learning task aims to classify genetic mutations based on text evidence from clinical literature with promising performance. We develop a novel multi-view machine learning framework with ensemble classification models to solve the problem. During the Challenge, feature combinations derived from three views including document view, entity text view, and entity name view, which complements each other, are comprehensively explored. As the final solution, we submitted an ensemble of nine basic gradient boosting models which shows the best performance in the evaluation. The approach scores 0.5506 and 0.6694 in terms of logarithmic loss on a fixed split in stage-1 testing phase and 5-fold cross validation respectively, which also makes us ranked as a top-1 team1 out of more than 1300 solutions in NIPS 2017 Competition Track IV. Copyright © 2018, The Authors. All rights reserved.

关键词： Machine learning

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Roadmap on Electronic Structure Codes in the Exascale Era

arXiv

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arXiv 2022年

作者： Gavini, Vikram Baroni, Stefano Blum, Volker Bowler, David R. Buccheri, Alexander Chelikowsky, James R. Das, Sambit Dawson, William Delugas, Pietro Dogan, Mehmet Draxl, Claudia Galli, Giulia Genovese, Luigi Giannozzi, Paolo Giantomassi, Matteo Gonze, Xavier Govoni, Marco Gulans, Andris Gygi, François Herbert, John M. Kokott, Sebastian Kühne, Thomas D. Liou, Kai-Hsin Miyazaki, Tsuyoshi Motamarri, Phani Nakata, Ayako Pask, John E. Plessl, Christian Ratcliff, Laura E. Richard, Ryan M. Rossi, Mariana Schade, Robert Scheffler, Matthias Schütt, Ole Suryanarayana, Phanish Torrent, Marc Truflandier, Lionel Windus, Theresa L. Xu, Qimen Yu, Victor W.-Z. Perez, Danny Department of Mechanical Engineering University of Michigan Ann ArborMI48109 United States SISSA ISAS Trieste Trieste34136 Italy IOM-CNR Trieste Trieste34136 Italy Duke University DurhamNC27708 United States London Centre for Nanotechnology LondonWC1H 0AH United Kingdom WPI-MANA National Institute for Materials Science Ibaraki305-0044 Japan Humboldt-Universität zu Berlin Berlin10117 Germany McKetta Department of Chemical Engineering University of Texas at Austin AustinTX78712 United States Center for Computational Materials Oden Institute University of Texas at Austin AustinTX78712 United States Department of Physics University of Texas at Austin AustinTX78712 United States RIKEN Center for Computational Science Hyogo Kobe650-0047 Japan Pritzker School of Molecular Engineering University of Chicago ChicagoIL60637 United States Materials Science Division Argonne National Laboratory LemontIL60439 United States Université Grenoble Alpes MEM L_Sim GrenobleF-38000 France University of Udine Udine33100 Italy IMCN Université catholique de Louvain Louvain-la-neuve Belgium University of Latvia RīgaLV-1586 Latvia University of California DavisCA95616 United States Department of Chemistry & Biochemistry The Ohio State University ColumbusOH43210 United States Berlin14195 Germany Dynamics of Condensed Matter Center for Sustainable Systems Design Chair of Theoretical Chemistry Paderborn University D-33098 Germany Paderborn Center for Parallel Computing Paderborn University D-33098 Germany Department of Computational and Data Sciences Indian Institute of Science Karnataka Bengaluru560012 India Lawrence Livermore National Laboratory LivermoreCA94550 United States Department of Computer Science Paderborn University D-33098 Germany Centre for Computational Chemistry School of Chemistry University of Bristol BristolBS8 1TS United Kingdom Ames National Laboratory AmesIA50011 United States Iowa State University AmesIA50

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing. Copyright © 2022, The Authors. All rights reserved.

关键词： Electronic structure

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Recent progress and trends in predictive visual analytics

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Frontiers of Computer Science 2017年第2期11卷 192-207页

作者： Junhua LU Wei CHEN Yuxin MA Junming KE Zongzhuang LI Fan ZHANG Ross MACIEJEWSKI State Key Lab of Computer Aided Design and Computer Graphics Zhejiang University Hangzhou 310058 China College of Science Zhejiang University of Technology Hangzhou 310023 China College of Computer Science and Technology Zhejiang University of Technology Hangzhou 310023 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85287-8809 USA

A wide variety of predictive analytics techniques have been developed in statistics, machine learning and data mining; however, many of these algorithms take a black-box approach in which data is input and future predictions are output with no insight into what goes on during the process. Unfortunately, such a closed system approach often leaves little room for injecting domain expertise and can result in frustration from analysts when results seem snurious or confusing. In order to allow for more human-centric approaches, the visualization community has begun developing methods to enable users to incorporate expert knowledge into the pre- diction process at all stages, including data cleaning, feature selection, model building and model validation. This paper surveys current progress and trends in predictive visual ana- lytics, identifies the common framework in which predictive visual analytics systems operate, and develops a summariza- tion of the predictive analytics workfiow.

关键词： predictive visual analytics visualization visual analytics data mining predictive analysis

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