检索结果-内蒙古大学图书馆

47th International Conference on computers and Industrial engineering: How Digital Platforms and Industrial engineering are Transforming Industry and Services, CIE 2017

作者： Wu, Zhenning Wang, Lixing Li, Qinya Colleage of Information and System Engineering Northeastern University Shenyang Liaoning China School of Computer Science and Engineering Northeastern University Shenyang Liaoning China Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai China

Wireless Sensor Networks (WSNs) use thousands of randomly scattered sensors to perform tasks such as data collection, processing, and transmission. However, the lifetime of WSNs depends on the limited power of batteries in sensor nodes. In this study, we propose a system to extend the lifetime of WSNs. The system has two main functions, one is optimizing the communication route and the other one is considering energy balance among sensor nodes in WSNs. To optimize route, three algorithms are designed for different sizes of WSNs. First, a random path algorithm is provided to obtain feasible routes randomly based on the step-by-step decomposition of a small network. Then, algorithms used in route selection problems: Dijkstra algorithm and Genetic Algorithm (GA) are analyzed. Finally, simulation is conducted to test the merits and demerits of these three algorithms as well as to compare their accuracy and efficiency in different networks. For energy balance, we calculate the importance of the degree and energy portion of each sensor node. Thus, we can determine which node requires increased battery capacity or additional attention. The strategies proposed in this system are different from existing common approaches that focus on cluster sensor nodes and balance energy consumption. The present study emphasizes route optimization in addition to considering energy balance.

关键词： Energy balance

来源：评论

学校读者我要写书评

暂无评论

Collision-free kinematics for redundant manipulators in dynamic scenes using optimal reciprocal velocity obstacles

arXiv

引用

arXiv 2018年

作者： Zhao, Liangliang Zhao, Jingdong Liu, Hong Manocha, Dinesh State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Department of Computer Science and Electrical & Computer Engineering University of Maryland at College Park MD United States

We present a novel algorithm for collision-free kinematics of multiple manipulators in a shared workspace with moving obstacles. Our optimization-based approach simultaneously handles collision-free constraints based on reciprocal velocity obstacles and inverse kinematics constraints for high-DOF manipulators. We present an efficient method based on particle swarm optimization that can generate collision-free configurations for each redundant manipulator. Furthermore, our approach can be used to compute safe and oscillation-free trajectories in a few milli-seconds. We highlight the real-time performance of our algorithm on multiple Baxter robots with 14-DOF manipulators operating in a workspace with dynamic obstacles. Videos are available at https://***/view/collision-free-kinematics. Copyright © 2018, The Authors. All rights reserved.

关键词： Inverse problems

来源：评论

学校读者我要写书评

暂无评论

Preface

Advances in Intelligent Systems and Computing

引用

Advances in Intelligent systems and Computing 2019年 873卷 v-vi页

作者： Ören, Tuncer De Rango, Floriano School of Electrical Engineering and Computer Science University of Ottawa OttawaON Canada Department of Informatics Electronics and System Engineering University of Calabria Modeling Rende Italy

来源：评论

学校读者我要写书评

暂无评论

MedShapeNet - A Large-Scale Dataset of 3D Medical Shapes for computer Vision

arXiv

引用

arXiv 2023年

作者： Li, Jianning Zhou, Zongwei Yang, Jiancheng Pepe, Antonio Gsaxner, Christina Luijten, Gijs Qu, Chongyu Zhang, Tiezheng Chen, Xiaoxi Li, Wenxuan Wodzinski, Marek Friedrich, Paul Xie, Kangxian Jin, Yuan Ambigapathy, Narmada Nasca, Enrico Solak, Naida Melito, Gian Marco Vu, Viet Duc Memon, Afaque R. Schlachta, Christopher De Ribaupierre, Sandrine Patel, Rajnikant Eagleson, Roy Chen, Xiaojun Mächler, Heinrich Kirschke, Jan Stefan de la Rosa, Ezequiel Christ, Patrick Ferdinand Li, Hongwei Bran Ellis, David G. Aizenberg, Michele R. Gatidis, Sergios Küstner, Thomas Shusharina, Nadya Heller, Nicholas Andrearczyk, Vincent Depeursinge, Adrien Hatt, Mathieu Sekuboyina, Anjany Löffler, Maximilian Liebl, Hans Dorent, Reuben Vercauteren, Tom Shapey, Jonathan Kujawa, Aaron Cornelissen, Stefan Langenhuizen, Patrick Ben-Hamadou, Achraf Rekik, Ahmed Pujades, Sergi Boyer, Edmond Bolelli, Federico Grana, Costantino Lumetti, Luca Salehi, Hamidreza Ma, Jun Zhang, Yao Gharleghi, Ramtin Beier, Susann Sowmya, Arcot Garza-Villarreal, Eduardo A. Balducci, Thania Angeles-Valdez, Diego Souza, Roberto Rittner, Leticia Frayne, Richard Ji, Yuanfeng Ferrari, Vincenzo Chatterjee, Soumick Dubost, Florian Schreiber, Stefanie Mattern, Hendrik Speck, Oliver Haehn, Daniel John, Christoph Nürnberger, Andreas Pedrosa, João Ferreira, Carlos Aresta, Guilherme Cunha, António Campilho, Aurélio Suter, Yannick Garcia, Jose Lalande, Alain Vandenbossche, Vicky Van Oevelen, Aline Duquesne, Kate Mekhzoum, Hamza Vandemeulebroucke, Jef Audenaert, Emmanuel Krebs, Claudia van Leeuwen, Timo Vereecke, Evie Heidemeyer, Hauke Röhrig, Rainer Hölzle, Frank Badeli, Vahid Krieger, Kathrin Gunzer, Matthias Chen, Jianxu van Meegdenburg, Timo Dada, Amin Balzer, Miriam Fragemann, Jana Jonske, Frederic Rempe, Moritz Malorodov, Stanislav Bahnsen, Fin H. Seibold, Constantin Jaus, Alexander Marinov, Zdravko Jaeger, Paul F. Stiefelhagen, Rainer Santos, Ana Sofia Lindo, Mariana Ferreira, André Alves, Victor Kamp, Michael Abourayya, Amr Nensa, Felix Hörst, Fabian Brehmer, Alexander Hein Girardetstraße 2 Essen45131 Germany Graz University of Technology Inffeldgasse 16c Graz8010 Austria Graz Austria The Department of Computer Science Johns Hopkins University Malone Hall 3400 N Charles St BaltimoreMD21218 United States Rte Cantonale Lausanne1015 Switzerland The Department of Measurement and Electronics AGH University of Science and Technology Krakow Poland Sierre Switzerland Department of Biomedical Engineering University of Basel Hegenheimermattweg Allschwil167C CH-4123 Switzerland The Boston College 140 Commonwealth Ave Chestnut HillMA02467 United States University Hospital B7-200 339 Windermere Road LondonN6A 5A5 Canada The Department of Radiology Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai200240 China The Research Center for Connected Healthcare Big Data ZhejiangLab Zhejiang Hangzhou311121 China The Faculty of Statistics Technical University Dortmund August-Schmidt-Straße 1 Dortmund44227 Germany The Institute of Mechanics Graz University of Technology Kopernikusgasse 24/IV Graz8010 Austria The Institute of Biomedical Manufacturing and Life Quality Engineering State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China The Department of Cardiac Surgery Medical University Graz Auenbruggerplatz 29 Graz8036 Austria The Department of Diagnostic and Interventional Radiology University Hospital Giessen Justus-Liebig-University Giessen Klinikstraße 33 Giessen35392 Germany The Department of Mechanical Engineering Mehran University of Engineering and Technology Jamshoro Sindh76062 Pakistan The Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China The Geschäftsführender Oberarzt Abteilung für Interventionelle und Diagnostische Neuroradiologie Universitätsklinikum der Technischen Universität München Ismaningerstr. 22 München81675 Germany icometrix Kolonel Be

Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publications in premier vision conferences as well as the growing popularity of ShapeNet (about 51,300 models) and Princeton ModelNet (127,915 models). For the medical domain, we present a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. As of today, MedShapeNet includes 23 datasets with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface (API) and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Exemplary, we present use cases in the fields of classification of brain tumors, skull reconstructions, multi-class anatomy completion, education, and 3D printing. In future, we will extend the data and improve the interfaces. The project pages are: https://***/ and https://***/Jianningli/*** Codes 68T01 © 2023, CC BY.

关键词： Large dataset

来源：评论

学校读者我要写书评

暂无评论

Correction: Improving Pelvic Floor Muscle Training Adherence Among Pregnant Women: Validation Study

引用

JMIR human factors 2022年第2期9卷 e38175页

作者： Aida Jaffar Sherina Mohd-Sidik Chai Nien Foo Novia Admodisastro Sobihatun Nur Abdul Salam Noor Diana Ismail Department of Psychiatry Faculty of Medicine and Health Sciences Universiti Putra Malaysia Selangor Malaysia. Primary Care Unit Faculty of Medicine and Defence Health Universiti Pertahanan Nasional Malaysia Wilayah Persekutuan Malaysia. Department of Population Medicine Universiti Tunku Abdul Rahman Selangor Malaysia. Software Engineering & Information System Department Faculty of Computer Science & Information Technology Universiti Putra Malaysia Selangor Malaysia. School of Multimedia Technology and Communication College of Arts and Sciences Universiti Utara Malaysia Kedah Malaysia. Klinik Kesihatan Bt 9 Cheras Ministry of Health Selangor Malaysia.

[This corrects the article DOI: 10.2196/30989.].

关键词：

来源：评论

学校读者我要写书评

暂无评论

HARNESSING DIGITAL PATHOLOGY AND CAUSAL LEARNING TO IMPROVE EOSINOPHILIC ESOPHAGITIS DIETARY TREATMENT ASSIGNMENT

arXiv

引用

arXiv 2023年

作者： Aknin, Eliel Larey, Ariel Caldwell, Julie M. Collins, Margaret H. Rothenberg, Marc E. Savir, Yonatan Abonia, Juan P. Aceves, Seema S. Arva, Nicoleta C. Chehade, Mirna Dellon, Evan S. Gonsalves, Nirmala Gupta, Sandeep K. Leung, John Peterson, Kathryn A. Shoda, Tetsuo Spergel, Jonathan M. Department of Physiology Biophysics and System Biology Faculty of Medicine Technion Israel Institute of Technology Haifa Israel Faculty of Industrial Engineering Technion Israel Institute of Technology Haifa Israel Faculty of Computer Science Technion Israel Institute of Technology Haifa Israel Division of Allergy and Immunology Cincinnati Children's Hospital Medical Center CincinnatiOH United States Dept. of Pediatrics University of Cincinnati College of Medicine CincinnatiOH United States Division of Pathology and Laboratory Medicine Cincinnati Children's Hospital Medical Center CincinnatiOH United States Division of Allergy and Immunology University of California at San Diego Rady Children's Hospital San DiegoCA United States Dept. of Pathology and Laboratory Ann and Robert H Lurie Children's Hospital Northwestern University Feinberg School of Medicine ChicagoIL United States Mount Sinai Center for Eosinophilic Disorders Icahn School of Medicine at Mount Sinai New YorkNY United States Division of Gastroenterology and Hepatology University of North Carolina School of Medicine Chapel HillNC United States Division of Gastroenterology and Hepatology Northwestern University Feinberg School of Medicine ChicagoIL United States Division of Pediatric Gastroenterology Hepatology and Nutrition Children's of Alabama University of Alabama at Birmingham BirminghamAL United States Boston Specialists BostonMA United States Division of Gastroenterology University of Utah Salt Lake CityUT United States Division of Allergy and Immunology Children's Hospital of Philadelphia Dept. of Pediatrics Perelman School of Medicine The University of Pennsylvania PhiladelphiaPA United States

Eosinophilic esophagitis (EoE) is a chronic, food antigen-driven, allergic inflammatory condition of the esophagus associated with elevated esophageal eosinophils. EoE is a top cause of chronic dysphagia after GERD. Diagnosis of EoE relies on counting eosinophils in histological slides, a manual and time-consuming task that limits the ability to extract complex patient-dependent features. The treatment of EoE includes medication and food elimination. A personalized food elimination plan is crucial for engagement and efficiency, but previous attempts failed to produce significant results. In this work, on the one hand, we utilize AI for inferring histological features from the entire biopsy slide, features that cannot be extracted manually. On the other hand, we develop causal learning models that can process this wealth of data. We applied our approach to the 'Six-Food vs. One-Food Eosinophilic Esophagitis Diet Study', where 112 symptomatic adults aged 18-60 years with active EoE were assigned to either a six-food elimination diet (6FED) or a one-food elimination diet (1FED) for six weeks. Our results show that the average treatment effect (ATE) of the 6FED treatment compared with the 1FED treatment is not significant, that is, neither diet was superior to the other. We examined several causal models and show that the best treatment strategy was obtained using T-learner with two XGBoost modules. While 1FED only and 6FED only provide improvement for 35%-38% of the patients, which is not significantly different from a random treatment assignment, our causal model yields a significantly better improvement rate of 58.4%. This study illustrates the significance of AI in enhancing treatment planning by analyzing molecular features' distribution in histological slides through causal learning. Our approach can be harnessed for other conditions that rely on histology for diagnosis and treatment. Copyright © 2023, The Authors. All rights reserved.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Cluster-Based Saliency-Guided Content-Aware Image Retargeting

引用

Journal of Electronic science and Technology 2017年第2期15卷 141-146页

作者： Li-Wei Kang Ching-Yu Tseng Chao-Long Jheng Ming-Fang Weng Chao-Yung Hsu Graduate School of Engineering Science and Technology and the Department of Computer Science and Information Engineering MPI Corporation Hsinchu Changing Information Technology Inc.Hsinchu 308 Institute for Information Industry Taipei 106 automation and Instrumentation System Development Sec. China Steel CorporationKaohsiung 81233

Straightforward image resizing operators without considering image contents （e.g., uniform scaling） cannot usually produce satisfactory results, while content-aware image retargeting aims to arbitrarily change image size while preserving visually prominent features. In this paper, a cluster-based saliency-guided seam carving algorithm for content- aware image retargeting is proposed. To cope with the main drawback of the original seam carving algorithm relying on only gradient-based image importance map, we integrate a gradient-based map and a cluster-based saliency map to generate a more reliable importance map, resulting in better single image retargeting results. Experimental results have demonstrated the efficacy of the proposed algorithm.

关键词： Index Terms--Content-aware image retargeting image resizing multimedia adaptation saliency detection seam carving.

来源：评论

学校读者我要写书评

暂无评论

Distributed system for Detecting the Malware in LAN

Distributed System for Detecting the Malware in LAN

引用

International Scientific and Technical Conference on computer science and Information Technologies

作者： George Markowsky Oleg Savenko Anatoliy Sachenko Department of Computer Science Missouri University of Science and Technology Rolla USA Department of Computer Engineering and System Programming Khmelnytsky National University Khmelnytsky Ukraine Department of Informatics Kazimierz Pulaski University of Technology and Humanities in Radom Radom Poland

The paper proposes the architecture of distributed multilevel detection system of malicious software in local area networks. Its feature is the synthesis of its requirements of distribution, decentralization, multilevel. This allows you to use it autonomously. In addition, the feature of autonomous program modules of the system is the same organization, which allows the exchange of knowledge in the middle of the system, which, unlike the known systems, allows you to use the knowledge gained by separate parts of the system in other parts. The developed system allows to fill it with subsystems of detection of various types of malicious software in local area networks.

关键词： Architecture Distributed system Malware Local area networks

来源：评论

学校读者我要写书评

暂无评论

Performance evaluation of anti-radiation based on the gamma degradation process

引用

science China(Technological sciences) 2017年第4期60卷 501-509页

作者： SONG BingHua ZHOU ZhongBao MA ChaoQun JIN Guang GENG ShaoFeng School of Business Administration Hunan University Changsha 410082 China College of Information System and Management National University of Defense Technology Changsha 410073 China College of Computer Science and Electronic Engineering Hunan University Changsha 410082 China

In the environment of space radiation, the high-energy charged particles or high-energy photons acting on a spacecraft can cause either temporary device degradation or permanent failure. The traditional probability model is difficult to obtain reliable estimation of unit radiation resistance performance with small samples. Considering that different products will change differently after high-energy particle radiation, we construct a model based on the gamma degradation process. This model can efficiently describe the law of unit radiation resistance variation with the total radiation dose levels under the effect of the total dose and displacement damage. Finally, the proposed model is used to assess the anti-radiation performance of the N-channel power MOSFET device STRH60N20FSY3 produced by STM to obtain average unit radiation resistance, survival probability, survival function, etc.

关键词： performance evaluation unit radiation resistance gamma degradation process survival probability

来源：评论

学校读者我要写书评

暂无评论

Self-adaptation of chimera states

引用

Physical Review E 2019年第1期99卷 010201(R)-010201(R)页

作者： Nan Yao Zi-Gang Huang Hai-Peng Ren Celso Grebogi Ying-Cheng Lai Department of Applied Physics Xi'an University of Technology Xi'an 710048 China The Key Laboratory of Biomedical Information Engineering of Ministry of Education National Engineering Research Center of Health Care and Medical Devices The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs and Institute of Health and Rehabilitation Science School of Life Science and Technology Xi'an Jiaotong University Xi'an 710049 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an 710048 China Institute for Complex Systems and Mathematical Biology King's College University of Aberdeen Aberdeen AB24 3UE United Kingdom School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA Department of Physics Arizona State University Tempe Arizona 85287 USA

Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve their robustness? We uncover a self-adaptation behavior by which, upon a spatially localized perturbation, the coherent component of the chimera state spontaneously drifts to an optimal location as far away from the perturbation as possible, exposing only its incoherent component to the perturbation to minimize the disturbance. A systematic numerical analysis of the evolution of the spatiotemporal pattern of the chimera state towards the optimal stable state reveals an exponential relaxation process independent of the spatial location of the perturbation, implying that its effects can be modeled as restoring and damping forces in a mechanical system and enabling the articulation of a phenomenological model. Not only is the model able to reproduce the numerical results, it can also predict the trajectory of drifting. Our finding is striking as it reveals that, inherently, chimera states possess a kind of “intelligence” in achieving robustness through self-adaptation. The behavior can be exploited for the controlled generation of chimera states with their coherent component placed in any desired spatial region of the system.

关键词： Chimera states Collective dynamics Coupled oscillators Chaos & nonlinear dynamics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：