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Nonlinear internal wave run-up on impermeable steep slopes

Journal of Offshore Mechanics and Arctic engineering 2009年第4期131卷 1-5页

作者： Tseng, I-Fan Chen, Chen-Yuan Kuo, Hui-Ming Department of Marine Environment and Engineering National Sun Yat-Sen University Kaohsiung 80424 Taiwan Department of Computer Science National Pingtung University of Education No. 4-18 Ming Shen Rd. Pingtung 90003 Taiwan Department of Management Information System Yung-Ta Institute of Technology and Commerce Lin-Luoh Pingtung 90941 Taiwan Doctoral Program in Management National Kaohsiung First University of Science and Technology Kaohsiung Taiwan Department of Logistics Management Shu-Te University Yen Chau Kaohsiung 82445 Taiwan

Laboratory experiments were conducted to investigate the run-up of internal solitary waves (ISWs) on steep uniform slopes in a two-layered fluid system with a free surface. A 12 m long wave flume, which incorporated a movable vertical gate for generating ISWs, was used in the experiments. A steep uniform slope was modeled at one end of the flume. In the present study we looked at internal waves with small and large amplitudes using a steep uniform slope (from one of Θ=30, 50, 60, 90, 120, and 130 deg) much longer than those previously published in the literature. Results collected from a wide range of experimental runs show that the run-up height depends on the planar slope, while the breaking depth is only antecedent to the amplitude of an ISW. The overall quantitative agreement with the linear feature aspects of the incident wave amplitude is encouraging. Copyright © 2009 by ASME.

关键词： Arctic engineering

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A comparison of training algorithms for DHP adaptive critic neurocontrol

A comparison of training algorithms for DHP adaptive critic ...

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International Joint Conference on Neural Networks (IJCNN)

作者： G.G. Lendaris T.T. Shannon A. Rustan Systems Science Ph.D. Program and Electrical & Computer Engineering Department Portland State University USA

A variety of alternate training strategies for implementing the dual heuristic programming (DHP) method of approximate dynamic programming in the neurocontrol context are explored. The DHP method of controller training has been successfully demonstrated by a number of authors on a variety of control problems in recent years, but no unified view of the implementation details of the method has yet emerged. A number of options are described for sequencing the training of the controller and critic networks in DHP implementations. Results are given about their relative efficiency and the quality of the resulting controllers for two benchmark control problems.

关键词： Neural networks Shape control Dynamic programming Equations Design optimization Amorphous materials Design methodology Feedback loop Supervised learning Process design

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Multi-tenant Cloud SaaS Application for a meeting to task transition via deep learning models

Multi-tenant Cloud SaaS Application for a meeting to task tr...

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Artificial Intelligence and Internet of Things (GCAIoT), IEEE Global Conference

作者： Viktor Walter-Tscharf Department of Information Engineering and Computer Science Doctoral Program Industrial Innovation Fondazione Bruno Kessler University of Trento European Institute of Innovation and Technology

ISBN: (纸本)9798350309850

Thought digitalisation and the post pandemic period online meetings increase by 12.9% and number of attendees by 13.5%. According to Zoom, Google Meets, and MS Teams they collectively increased there amount of active users from March 2020 until june 2021 by 253%. Additionally virtual meetings are becoming inefficient, unproductive and unstructured, where results are not documented correctly. The intention is to shift those statistics by revolutionising the way online meeting are held. The paper outlines the technical requirements for a user-friendly web application that allows to reproduce a virtual meeting including agreements, its participants interactions and highlighting relevant sequences, is outlined. The developed AI meeting wizard autonomously documents the discussed content in the form of notes, to-dos tasks and integrates them directly into task management, mail or calendar tools. Reinforcing the focus on the discussion by increased interaction and productivity instead of task management and note taking.

关键词： Technical requirements Productivity Pandemics Software as a service Speech recognition Internet of Things Task analysis

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Dynamic programming Algorithm using Furniture Industry 0/1 Knapsack Problem 5

Dynamic Programming Algorithm using Furniture Industry 0/1 K...

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5th International Conference on Cybernetics and Intelligent systems, ICORIS 2023

作者： Anditta, Mietha Amartya, Natashya Warnars, Laurens Spits Warnars, Harco Leslie Hendric Spits Ramadhan, Arief Siswanto, Teddy Mantoro, Teddy Noordin, Nurulhuda Bina Nusantara University School of Computer Science Computer Science Departement Jakarta11530 Indonesia Bina Nusantara University School of Information Systems Information Systems Departement Jakarta11530 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Departement Jakarta11530 Indonesia Telkom University Pjj Informatika Bandung40257 Indonesia Trisakti University Information Systems Department Jakarta11440 Indonesia Sampoerna University Faculty of Engineering and Technology Jakarta12760 Indonesia Universiti Teknologi Mara School of Computing Sciences College of Computing Informatics and Mathematics Selangor Malaysia

ISBN: (纸本)9798350369489

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset. © 2023 IEEE.

关键词： Dynamic programming

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Comparative study of leaf image recognition with a novel learning-based approach

Comparative study of leaf image recognition with a novel lea...

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science and Information Conference (SAI)

作者： Jou-Ken Hsiao Li-Wei Kang Ching-Long Chang Chih-Yang Lin Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan Graduate School of Engineering Science and Technology-Doctoral Program National Yunlin University of Science and Technology Yunlin Taiwan Department of Computer Science and Information Engineering Asia University Taichung Taiwan

Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, we conduct a comparative study on leaf image recognition and propose a novel learning-based leaf image recognition technique via sparse representation (or sparse coding) for automatic plant identification. In our learning-based method, in order to model leaf images, we learn an overcomplete dictionary for sparsely representing the training images of each leaf species. Each dictionary is learned using a set of descriptors extracted from the training images in such a way that each descriptor is represented by linear combination of a small number of dictionary atoms. Moreover, we also implement a general bag-of-words (BoW) model-based recognition system for leaf images, used for comparison. We experimentally compare the two approaches and show unique characteristics of our sparse coding-based framework. As a result, efficient leaf recognition can be achieved on public leaf image dataset based on the two evaluated methods, where the proposed sparse coding-based framework can perform better.

关键词： Image recognition Dictionaries Training Feature extraction Shape Vectors Image coding

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Cross-camera complementary vehicle matching via feature expandsion for video forensics

Cross-camera complementary vehicle matching via feature expa...

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IEEE International Symposium on Consumer Electronics (ISCE)

作者： Chao-Yung Hsu Chih-Yang Lin Li-Wei Kang Hong-Yuan Mark Liao Institute of Information Science Academia Sinica Taipei Taiwan Department of Computer Science and Information Engineering Asia University Taichung Taiwan Graduate School of Engineering Science and Technology-Doctoral Program and Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9781467361989

In this paper, we will investigate a more challenging vehicle matching problem. The problem is formulated as invariant image feature matching among opposite viewpoints of cameras, i.e. complementary object matching. For example, a front vehicle object may be given as a query to retrieve a rear vehicle object of the same vehicle. To solve the complementary object matching, invariant image feature is first extracted based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, the ASIFT feature is expanded via a special vehicle database. As a result, cross-camera vehicle matching with the help of complementary part can be greatly improved. Experimental results demonstrate the effectiveness of the proposed algorithm and the feasibility to video forensics applications.

关键词： Vehicles Cameras Databases Feature extraction Visualization Digital forensics

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A Systematic Integrated Literature Review of Clinical Data Management Platforms of HL7 FHIR

A Systematic Integrated Literature Review of Clinical Data M...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Franz Frederik Walter Viktor Walter-Tscharf Department of Information Engineering and Computer Science Fondazione Bruno Kessler University of Trento European Institute of Innovation and Technology Doctoral Program Industrial Innovation

This study is dedicated to a critical investigation of the existing approaches toward a data visualization management platform based on Fast Health Interoperability Resources (FHIR). Despite the growing popularity of FHIR, the available evidence provides a compelling reason to believe that its use is still accompanied by a significant number of technical challenges. Therefore, the development of tools to ensure its convenient visualization remains a pressing need for a variety of stakeholders operating in the healthcare industry. Results of the systematic literature review that included 26 studies provide valuable information about the most popular instruments in this area, such as the OpenEHR CKM approach. The review offers a critical discussion of the most important advantages and disadvantages of different approaches. It provides valuable recommendations for further research as well as practical recommendations concerning the best ways to utilize data visualization platforms based on FHIR. It defines the tradeoff of functionality versus the ease of dissemination as one of the most important problems facing most platforms and suggests avenues for developing additional tooling support for visualizing FHIR. The results of the research could be useful both for scientists and practitioners.

关键词： Industries Systematics Bibliographies Instruments Data visualization Pressing Medical services

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Exploring 3D Reconstruction with Drone Images: Advances and Challenges in Urban Environments 50

Exploring 3D Reconstruction with Drone Images: Advances and ...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Miranda Baldivieso, Thiago João da Silva Batista, Taise Grazielle Chagas, Fabio Suim Rodrigues Velho, Luiz Carlos Pacheco Ferreira Rosa, Paulo Fernando Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil State Institute of the Environment Inea RJ Rio de Janeiro Brazil Department of Science and Industry systems University of South-Eastern Norway Kongsberg Norway Department of Computer Graphics Institute for Pure and Applied Mathematics Rio de Janeiro Brazil Electrical Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (纸本)9781665464543

This working-in-progress paper aims to present a three-dimensional reconstruction using aerial images in different environments. The experiments were conducted with aircraft in both external and internal settings, starting with image acquisition, followed by the application of specific photogrammetry software-both commercial and open-source-and concluding with a qualitative evaluation of the results. © 2024 IEEE.

关键词： Aerial photography

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Classification of Land Cover from Sentinel-2 Imagery Using Supervised Classification Technique (Preliminary Study)

Classification of Land Cover from Sentinel-2 Imagery Using S...

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International Conference on Information Management and Technology (ICIMTech)

作者： Eka Miranda Achmad Benny Mutiara Ernastuti Wahvu Catur Wibowo Information Systems Department Doctoral Program in Information Technology Gunadarma University Jakarta Indonesia Faculty of Computer Science and Information Technology Gunadarma University Jakarta Indonesia Computer Science Faculty Universitas Jakarta Indonesia

This paper intended to classify land cover of high-resolution satellite image using supervised classification method. The object of this research was the land cover image of the central java area in Indonesia which chosen as an area observed with the cloud cover consideration. The Satellite image was obtained from Sentinel-2 through https://***. Supervised Classification and ArcMap 10.5 was used to classified image object. This research classified the land cover into four classifications class namely Water, Forest, Urban and Bare Land due to show the main classes in the Land Cover Classification of RSNI-l National Standardization Body of Indonesia, RSNI-l was used as reference for classification process. The confusion matrix used to calculate classification accuracy value. Subsequently, confusion matrix results compared to the truth information. The truth information was derived from the actual value of RASTERVALUE obtained from Google Earth. This research shown supervised classification maximum-likelihood classification has been classified land cover into four class (forest, water body, urban and bare land) with overall accuracy = 1 and kappa value = 0.4896. This result showed this research got moderate kappa accuracy value but high overall accuracy value. High accuracy value reached due to fully supervised experiment during classification process.

关键词： Satellites Forestry Training Java Probability Standardization Vegetation mapping

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Precision Oral Medicine: A DPR Segmentation and Transfer Learning Approach for Detecting Third Molar Compress Inferior Alveolar Nerve

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IEEE Journal of Translational engineering in Health and Medicine 2025年

作者： Lin, Yuan-Jin Chen, Shih-Lun Mao, Yi-Cheng Chen, Tsung-Yi Peng, Cheng-Hao Tsai, Tzu-Hsiang Li, Kuo-Chen Chen, Chiung-An Tu, Wei-Chen Abu, Patricia Angela R. National Cheng Kung University Department of Program on Semiconductor Manufacturing Technology Academy of Innovative Semiconductor and Sustainable Manufacturing Tainan City 701401 Taiwan Chung Yuan Christian University Department of Electronic Engineering Taoyuan City 32023 Taiwan Taoyuan Chang Gang Memorial Hospital Department of Operative Dentistry Taoyuan City 33305 Taiwan Feng Chia University Department of Electronic Engineering Taichung city 40724 Taiwan Chung Yuan Christian University Taoyuan City 32023 Taiwan Chung Yuan Christian University Department of Information Management Taoyuan City 32023 Taiwan Ming Chi University of Technology Department of Electronic Engineering New Taipei City 243303 Taiwan National Cheng Kung University Department of Electrical Engineering Tainan city 701401 Taiwan Ateneo de Manila University Department of Information Systems and Computer Science Quezon City Philippines

Objective: Extraction of the third molar of the mandible is one of the most common oral surgical procedures. Preoperative monitoring and assessment are crucial to mitigate neurological risks. Identifying whether the third molar in the mandible compresses the inferior alveolar nerve still relies on dental professionals, a task that is repetitive and time-consuming. Thus, the primary objective is to utilize dental panoramic radiography for image processing and classify whether the third molar compresses the inferior alveolar nerve, aiming to reduce the demand for CT images in symptom diagnosis and mitigate the risks associated with high-dose radiation. Technology or Method: This study proposes an innovative dental panoramic radiography segmentation technique to locate the third molar position. Subsequently, an innovative edge masking enhancement method is used to extract features of the inferior alveolar nerve and the third molar. Moreover, a transformer-based image detection model to consider whether the third molar compresses the inferior alveolar nerve. Results: The third molar position localization method achieved an accuracy rate of 97.92%, compared to recent research at least improved by 3.6% accuracy. Subsequently, innovative edge masking and image enhancement methods improve classification accuracy by 4.3%, when supplemented with computed tomography scan images for further evaluation, the maximum accuracy reached 98.45%, representing a 4.5% improvement compared to previous studies. Conclusions: The third molar position detection results will impact the identification of the inferior alveolar nerve compressed by the third molar. Through the innovative edge region segmentation algorithm can effectively distinguish this object, and the overall evaluation accuracy can be improved by approximately 3.8%. © 2013 IEEE.

关键词： Image Masking Image Segmentation Inferior Alveolar Nerve Object Detection Third Molar Vision Transformer

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