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11th International Symposium on Computing and Networking Workshops, CANDARW 2023

作者： Watanabe, Kaito Nakayama, Hirotaka Shiraki, Atsushi Ito, Tomoyoshi Hirata, Katsumi Hoshikawa, Naoto National Institute of Technology Oyama College Advanced Course General Engineering Program Oyama Japan National Astronomical Observatory of Japan Center for Computational Astrophysics Mitaka Japan Chiba University Graduate School of Engineering Chiba Japan National Institute of Technology Oyama College Department of Innovative Electrical and Electronic Engineering Oyama Japan University of Tsukuba Graduate School of Science and Tecnology Tsukuba Japan

ISBN: (纸本)9798350306941

In recent years, 3DCG-related industries have grown rapidly and the demand for 3DCG content has increased. However, 3DCG production requires special skills and a lot of time. In particular, the creation of background data requires a lot of human resources at the production site because the data is huge and complex. Therefore, we propose an automatic creation system that generates 3D background data for 3DCG production. The proposed system consists of three functions: 3D model generation, generation parameter optimization, and fitness evaluation. The user inputs a landscape photograph as idea information into the system, and the system optimizes the generation parameters so that the 3D object shape approximates the input image. To evaluate the accuracy of the system's performance, we observe the optimization process and the 3D object output when a previously generated fractal image or landscape photos are input. Experimental results show that the system accurately optimizes the generation parameters and generates 3D objects that are almost identical to the shape of the fractal image. In addition, the parameters were also optimized with a certain degree of accuracy for landscape photographs for which no specific solution had been determined. © 2023 IEEE.

关键词： Genetic algorithms

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B(s)→D(s)(*)M decays in the presence of final-state interactions

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Physical Review D 2025年第9期111卷 095020-095020页

作者： Albertus Hariwangsa Panuluh Satoshi Tanaka Hiroyuki Umeeda Department of Physics Education Faculty of Teacher Training and Education Sanata Dharma University Paingan Maguwohardjo Sleman Yogyakarta 55282 Indonesia Physics Program Graduate School of Advanced Science and Engineering Hiroshima University 1-3-1 Kagamiyama Higashi-Hiroshima 739-8526 Japan Scientific Computational Division Nippon Advanced Information Service (NAIS Co. Inc.) 416 Muramatsu Tokaimura Naka-gun Ibaraki 319-1112 Japan Center for Theoretical Physics and College of Physics Jilin University Changchun 130012 China China Center of Advanced Science and Technology Beijing 100190 China Institute of High Energy Physics Chinese Academy of Sciences Beijing 100049 China

In light of the recent data for B¯(s)→D(s)(*)P and B¯(s)→D(s)V decays, we perform a model-independent phenomenological analysis in the presence of quasielastic rescattering. With the Wilson coefficients including contributions beyond the standard model, the lifetimes of the B meson and Bd0−B¯d0 mixing are investigated to clarify correlations among the observables. We show that parameter regions for quasielastic rescattering, the size of color-suppressed tree amplitudes, and new physics are constrained due to the lifetime data. As a consequence, it is revealed that this scenario can be tested by the future LHCb measurement of the width difference in Bd0−B¯d0 mixing and semileptonic CP asymmetry.

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Early surveillance of rice bakanae disease using deep learning and hyperspectral imaging

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aBIOTECH 2024年第3期5卷 281-297页

作者： Sishi Chen Xuqi Lu Hongda Fang Anand Babu Perumal Ruyue Li Lei Feng Mengcen Wang Yufei Liu College of Biosystems Engineering and Food Science Zhejiang UniversityHangzhou 310058China State Key Laboratory of Rice Biology and Breeding Zhejiang UniversityHangzhou 310058China Computational Modeling and Nanoscale Processing Unit National Institute of Food TechnologyEntrepreneurship and Management-ThanjavurMinistry of Food Processing IndustriesThanjavur 613005India College of Environmental and Resource Sciences Zhejiang UniversityHangzhou 310058China Global Education Program for AgriScience Frontiers Graduate School of AgricultureHokkaido UniversitySapporo 060-8589Japan

Bakanae disease,caused by Fusarium fujikuroi,poses a significant threat to rice production and has been observed in most rice-growing *** disease symptoms caused by different pathogens may vary,including elongated and weak stems,slender and yellow leaves,and dwarfism,as *** disease is likely to cause necrosis of diseased seedlings,and it may cause a large area of infection in the field through the transmission of ***,early disease surveillance plays a crucial role in securing rice *** monitoring methods are both time-consuming and labor-intensive and cannot be broadly *** this study,a combination of hyperspectral imaging technology and deep learning algorithms were used to achieve in situ detection of rice seedlings infected with bakanae *** data were obtained on the 9th,15th,and 21st day after rice infection to explore the physiological and biochemical performance,which helps to deepen the research on the disease *** data were obtained over these same periods of infection,and a deep learning model,named Rice Bakanae Disease-Visual Geometry Group(RBD-VGG),was established by leveraging hyperspectral imaging technology and deep learning *** on this model,an average accuracy of 92.2%was achieved on the 21st day of *** also achieved an accuracy of 79.4%as early as the 9th *** characteristic wavelengths were extracted to increase the feasibility of using portable spectral equipment for field ***,the model offers an efficient and non-destructive surveillance methodology for monitoring bakanae disease,thereby providing an efficient avenue for disease prevention and control.

关键词： Bakanae disease Hyperspectral imaging Deep learning Early surveillance Disease monitoring

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Implementation of OpenMP and MPI hybrid parallelization to Monte Carlo dose simulation for particle therapy

Implementation of OpenMP and MPI hybrid parallelization to M...

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World Congress on Medical Physics and Biomedical Engineering

作者： Furuta, T. Ishikawa, K.L. Fukunishi, N. Noda, S. Takagi, S. Maeyama, T. Fukasaku, K. Himeno, R. RIKEN Computational Science Research Program Wako Japan University of Tokyo Department of Nuclear Engineering and Management Graduate School of Engineering Tokyo Japan RIKEN Nishina Center for Accelerator-Based Science Wako Japan RIKEN Advanced Center for Computing and Communication Wako Japan University of Tokyo Department of Mechanical Engineering Tokyo Japan Himon'ya Hospital Department of Neurosurgery Tokyo Japan

ISBN: (纸本)9783642293047

We report a successful implementation of the sharedmemory parallelization using OpenMP to the dose calculation by the Monte Carlo particle and heavy-ion transport code PHITS. The OpenMP shared-memory parallelization is better suited than the MPI distributed-memory parallelization which is originally implemented in the PHITS code in the case of human voxel data which requires a large memory space. We have confirmed that the same results can be obtained with and without the shared-memory parallelization by the modified PHITS code. Sufficiently high OpenMP parallelization efficiency (92.4% with 8 parallelized cores within a single node) is achieved even when the special treatment for accessing memory to avoid memory contentions is taken into account. We implement the OpenMP parallelization on top of the MPI parallelization originally included in PHITS so that the modified code works in a hybrid way such that the distributed-memory parallelization for different nodes by MPI and the shared-memory parallelization among the cores in a single node by OpenMP. The performance has been checked on supercomputers: RICC and K computer. © 2013 Springer-Verlag.

关键词： Supercomputers

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Applying the MVC EA-IRPM to reporting-guidelines in medicine: A strategy that is a web system 4

Applying the MVC EA-IRPM to reporting-guidelines in medicine...

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4th IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017

作者： Letouze, Patrick De Souza, J.I.M. Silva, Valeria Martins Climaco, Glaubos Chagas, F.B. Ishihara, Joao Y. Graduate Program of Computational Modeling of Systems Universidade Federal Do Tocantins Quadra 109 Norte Avenida NS-15 Palmas77001-090 Brazil Graduate Program of Systems' Engineering and Computation - PESC Universidade Federal Do Rio de Janeiro Rio de Janeiro Brazil Department of Informatics at the Universidade Federal Do Maranh/ Ao - UFMA Brazil Faculty of Computer Science Faculdade Pitagoras Imperatriz Imperatriz Brazil Faculty of Electrical Engineering Universidade de Brasília Brasília Brazil

ISBN: (纸本)9781509041794

Reporting-Guidelines in Medicine play an important role in promoting the quality of reports in health-related research. For instance, a poorly reported research may induce misinterpretation and inappropriate clinical settings. Basically, three major issues regarding Reporting-Guidelines in Medicine has to be addressed: (1) the existence of lots of reporting guidelines covering a broad spectrum of medical research increases the difficulties when reporting a medical research because it may not be clear which guidelines are applicable, or if all related guidelines are considered;(2) most guideline developers have not described how their guidance was developed, consequently tracking guidelines and features for evaluation, or even for correcting, may be not possible;(3) few guideline developers have evaluated the effectiveness of their guidance, then the real value that the guideline brings to reporting the research is not assured. Hence, we propose a solution to these three issues based on the Model-View-Controller Evolutionary Acquisition Interdisciplinary Research Project Management (MVC EA-IRPM) that is simultaneously a strategy and a web system for the development and management of reporting guidelines. © 2017 IEEE.

关键词： Clinical research

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A Parallel RatSlam C++ Library Implementation 2nd

A Parallel RatSlam C++ Library Implementation

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2nd Latin American Workshop on computational Neuroscience, LAWCN 2019

作者： de Souza Muñoz, Mauro Enrique Menezes, Matheus Chaves de Freitas, Edison Pignaton Cheng, Sen de Almeida Neto, Areolino de Oliveira, Alexandre César Muniz de Almeida Ribeiro, Paulo Rogério Federal University of Maranhão Av. dos Portugueses 1966 Bacanga São LuísMaranhão Brazil Graduate Program on Computer Science Federal University of Rio Grande do Sul Porto Alegre Brazil Computational Neuroscience Institute for Neural Computation Ruhr University Bochum Bochum Germany

ISBN: (纸本)9783030366353

RatSlam is a bio-inspired Simultaneous Location and Mapping (SLAM) algorithm used for autonomous mobile robots navigation tasks. This work presents a RatSlam algorithm implementation as a C++ library designed to take advantage of internal RatSlam modules parallelization. The RatSlam algorithm is presented with principal aspects of the library architecture design. Furthermore, its results using a well known RatSlam data set with a standard RatSlam implementation (OpenRatSLAM - Robot Operating System), and a Python implementation. The mapping found with the previous approaches and the proposed on this work were similar. Moreover, the execution times between the OpenRatSLAM and this C++ library was compared, with the proposed implementation having a lower execution time. Thus, the current implementation was validated and has some advantages against previous ones, which can be very relevant for real-time applications. © Springer Nature Switzerland AG 2019.

关键词： Robot Operating System

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Identify Non-mutational p53 Functional Deficiency in Human Cancers

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Genomics, Proteomics & Bioinformatics 2024年第5期22卷 85-98页

作者： Qianpeng Li Yang Zhang Sicheng Luo Zhang Zhang Ann L.Oberg David E.Kozono Hua Lu Jann N.Sarkaria Lina Ma Liguo Wang National Genomics Data Center China National Center for BioinformationBeijing 100101China Beijing Institute of Genomics Chinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China Division of Computational Biology Mayo Clinic College of Medicine and ScienceRochesterMN 55905USA Department of Radiation Oncology Dana-Farber Cancer Institute and Brigham and Women's HospitalBostonMA 02215USA Department of Biochemistry&Molecular Biology and Tulane Cancer Center Tulane University School of MedicineNew OrleansLA 70112USA Department of Radiation Oncology Mayo Clinic College of Medicine and ScienceRochesterMN 55905USA Department of Biochemistry and Molecular Biology Mayo Clinic College of Medicine and ScienceRochesterMN 55905USA Bioinformatics and Computational Biology Graduate Program University of Minnesota RochesterRochesterMN 55904USA

An accurate assessment of p53's functional statuses is critical for cancer genomic ***,there is a significant challenge in identifying tumors with non-mutational p53 inactivation which is not detectable through DNA *** undetected cases are often misclassified as p53-normal,leading to inaccurate prognosis and downstream association *** address this issue,we built the support vector machine(SVM)models to systematically reassess p53's functional statuses in TP53 wild-type(TP53^(WT))tumors from multiple The Cancer Genome Atlas(TCGA)***-validation demonstrated the good performance of the SVM models with a mean area under the receiver operating characteristic curve(AUROC)of 0.9822,precision of 0.9747,and recall of *** study revealed that a significant proportion(87%-99%)of TP53^(WT) tumors actually had compromised p53 *** analyses uncovered that these genetically intact but functionally impaired(termed as predictively reduced function of p53 or TP53^(WT)-pRF)tumors exhibited genomic and pathophysiologic features akin to TP53-mutant tumors:heightened genomic instability and elevated levels of ***,patients with TP53^(WT)-pRF tumors experienced significantly shortened overall survival or progression-free survival compared to those with predictively normal function of p53(TP53^(WT)-pN)tumors,and these patients also displayed increased sensitivity to platinum-based chemotherapy and radiation therapy.

关键词： Cancer Composite expression DNA mutation Machine learning p53 deficiency

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Agile parallel bioinformatics workflow management using Pwrake

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BMC Research Notes 2011年第1期4卷 1-8页

作者： Mishima, Hiroyuki Sasaki, Kensaku Tanaka, Masahiro Tatebe, Osamu Yoshiura, Koh-Ichiro Department of Human Genetics Nagasaki University Graduate School of Biomedical Sciences Nagasaki Nagasaki 1-12-4 Sakamoto Japan Nagasaki University Global Center of Excellence Program Nagasaki Nagasaki 1-12-4 Sakamoto Japan Center for Computational Sciences University of Tsukuba Tsukuba Ibaraki 1-1-1 Tennodai Japan Core Research for Evolutional Science and Technology Japan Science and Technology Agency Kawaguchi Saitama 4-1-8 Honcho Japan Departmentent of Computer Science Graduate School of Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki 1-1-1 Tennodai Japan

Background: In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error. Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. Findings. We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Conclusions: Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability

关键词： Ruby Iterative Development Agile Software Development Host Language Bioinformatics Domain

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NOMAD: nonlinear manifold decoders for operator learning 22

NOMAD: nonlinear manifold decoders for operator learning

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Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Jacob H. Seidman Georgios Kissas Paris Perdikaris George J. Pappas Graduate Program in Applied Mathematics and Computational Science University of Pennsylvania Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania Department of Electrical and Systems Engineering University of Pennsylvania

ISBN: (纸本)9781713871088

Supervised learning in function spaces is an emerging area of machine learning research with applications to the prediction of complex physical systems such as fluid flows, solid mechanics, and climate modeling. By directly learning maps (operators) between infinite dimensional function spaces, these models are able to learn discretization invariant representations of target functions. A common approach is to represent such target functions as linear combinations of basis elements learned from data. However, there are simple scenarios where, even though the target functions form a low dimensional submanifold, a very large number of basis elements is needed for an accurate linear representation. Here we present NOMAD, a novel operator learning framework with a nonlinear decoder map capable of learning finite dimensional representations of nonlinear submanifolds in function spaces. We show this method is able to accurately learn low dimensional representations of solution manifolds to partial differential equations while outperforming linear models of larger size. Additionally, we compare to state-of-the-art operator learning methods on a complex fluid dynamics benchmark and achieve competitive performance with a significantly smaller model size and training cost.

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A Neuro-Inspired Approach to Solve a Simultaneous Location and Mapping Task Using Shared Information in Multiple Robots Systems 15

A Neuro-Inspired Approach to Solve a Simultaneous Location a...

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15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018

作者： Menezes, Matheus Chaves De Freitas, Edison Pignaton Cheng, Sen De Oliveira, Alexandre Cesar Muniz De Almeida Ribeiro, Paulo Rogerio Graduate Program on Computer Science Federal University of Maranhão Sao Luis Brazil Computational Neuroscience Ruhr University Bochum Institute for Neural Computation Bochum Germany Department of Informatics Federal University of Maranhão Sao Luis Maranhao Brazil Department of Computer Engineering Federal University of Maranhão Sao Luis Maranhao Brazil

ISBN: (纸本)9781538695821

This paper presents a neuro-inspired mapping approach that uses partial information shared by multiple robots to reduce the time to create a map of an entire environment. Robots using a neurobiologically inspired algorithm, namely RatSLAM, map an environment sharing video information among themselves. RatSLAM, which is based on the navigation system present in the hippocampus of rodents' brain, has been widely used on simultaneous localization and mapping (SLAM) problem. This proposal has been able to generate suitable maps mainly when there is redundant information, e.g. a scene is seen more than once, since this fact activates local view cells that inject activity inside the pose cells via an excitatory link. The work here reported extends this approach by merging partial information acquired by multiple robots. The results from the performed experiments show that the final map built by two robots with shared information is similar to one built by two robots performing the same mapping task individually, i.e. without sharing information. However, the time spent to generate the whole map with the proposed shared approach was smaller than the one without the shared information. Thus, the current approach allows creating a complete map of an environment within a reduced time using multiple robots. © 2018 IEEE.

关键词： Mapping

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