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Conference on Lasers and Electro-Optics (CLEO)

作者： Kellen P. Arnold Joel B. Slaby Hannah M. Dattilo C. Alex Kaylor Ronald D. Schrimpf Daniel M. Fleetwood Stephen E. Ralph Robert Reed Sharon M. Weiss Interdisciplinary Materials Science Program Vanderbilt University Nashville TN USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Department of Electrical and Computer Engineering Vanderbilt University Nashville TN USA

We report a simple, vacuum-compatible fiber attach process for in situ study of grating-coupled photonic devices. The robustness of this technique is demonstrated on grating-coupled waveguides exposed to multiple X-ra... 详细信息

ISBN: (纸本)9798350369311

关键词： Optical fibers Radiation effects X-ray lasers Waveguide lasers Fiber gratings Robustness Optical fiber devices Arrayed waveguide gratings Photonics Optical arrays

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Faster Groebner bases for Lie derivatives of ODE systems via monomial orderings 49

Faster Groebner bases for Lie derivatives of ODE systems via...

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49th International Symposium on Symbolic and Algebraic Computation, ISSAC 2024

作者： Bessonov, Mariya Ilmer, Ilia Konstantinova, Tatiana Ovchinnikov, Alexey Pogudin, Gleb Soto, Pedro Department of Mathematics Cuny Nyc College of Technology New YorkNY United States Ph.D. Program in Computer Science Cuny Graduate Center New YorkNY United States Department of Mathematics Cuny Queens College New YorkNY United States Department of Mathematics Cuny Queens College United States Ph.D. Programs in Mathematics and Computer Science Cuny Graduate Center New YorkNY United States Lix Cnrs École Polytechnique Institute Polytechnique de Paris Paris France

ISBN: (纸本)9798400706967

Symbolic computation for systems of differential equations is often computationally expensive. Many practical differential models have a form of polynomial or rational ODE system with specified outputs. A basic symbolic approach to analyze these models is to compute and then symbolically process the polynomial system obtained by sufficiently many Lie derivatives of the output functions with respect to the vector field given by the ODE system. In this paper, we present a method for speeding up Gröbner basis computation for such a class of polynomial systems by using specific monomial ordering, including weights for the variables, coming from the structure of the ODE model. We provide empirical results that show improvement across different symbolic computing frameworks and apply the method to speed up structural identifiability analysis of ODE models. © 2024 ACM.

关键词： Polynomials

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Performance Analysis of Economic Model Predictive Control on a Solar-Powered Direct Contact Membrane Distillation System

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IFAC-PapersOnLine 2022年第33期55卷 13-19页

作者： Hichem Bessafa Ghania Khodja Chakir Messaoud Taous-Meriem Laleg-Kirati Electrical and Computer Engineering Program. Computer Electrical and Mathematical Science and Engineering (CEMSE) division. King Abdullah University of Science and Technology (KAUST) Ecole Polytechnique of Algiers Algeria National Institute for Research in Digital Science and Technology (INRIA) Paris-Saclay France

This paper proposes an economic model predictive control (EMPC) design for a Direct Contact Membrane Distillation powered by a solar collector system which aims at enhancing its economical performances. A differential algebraic equations-based model is used for the design of the EMPC control. Moreover, a nonlinear observer is developed for the estimation of the unmeasured state. A neural network is proposed to predict the unknown solar irradiance for future horizon where a solar model provides temperature predictions. The proposed control design has been validated in simulation using data provided by a partial differential equation-based model mimicking the real plant.

关键词： Direct contact membrane distillation Economic model predictive control differential algebraic equations nonlinear observer Long-short term memory neural network

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Multilevel Particle Filters for Partially Observed McKean-Vlasov Stochastic Differential Equations

arXiv

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arXiv 2024年

作者： Awadelkarim, Elsiddig Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia School of Data Science The Chinese University of Hong Kong Shenzhen China

In this paper we consider the filtering problem associated to partially observed McKean-Vlasov stochastic differential equations (SDEs). The model consists of data that are observed at regular and discrete times and the objective is to compute the conditional expectation of (functionals) of the solutions of the SDE at the current time. This problem, even the ordinary SDE case is challenging and requires numerical approximations. Based upon the ideas in [3, 12] we develop a new particle filter (PF) and multilevel particle filter (MLPF) to approximate the afore-mentioned expectations. We prove under assumptions that, for ϵ > 0, to obtain a mean square error of O(ϵ2) the PF has a cost per-observation time of O(ϵ−5) and the MLPF costs O(ϵ−4) (best case) or O(ϵ−4 log(ϵ)2) (worst case). Our theoretical results are supported by numerical experiments. © 2024, CC BY.

关键词： Mean square error

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Towards Explainability of Dimension Reduction Plots of Unsupervised Learning Model Outcomes

Towards Explainability of Dimension Reduction Plots of Unsup...

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IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology (CIBCB)

作者： Tony E. Astuhuaman Davila Daniel B. Hier Tayo Obafemi-Ajayi Computer Science Dept. Missouri State University Springfield MO USA Kummer Institute Missouri University of Science & Technology Rolla MO USA Engineering Program Missouri State University Springfield MO USA

ISBN: (数字)9798350356632

ISBN: (纸本)9798350356649

Dimension reduction methods are used to visualize the output of unsupervised learning models when applied to complex data. These techniques improve interpretability by transforming a high-dimension space to a lower-dimension space (usually 2D or 3D). The results are typically viewed as 2D scatter plots, and class centroids may be added to increase interpretability. Although useful, the relationship of these class centroids to the underlying feature space remains opaque. The innovative aspect of this work is to create a strong link between the dimension-reduced space and the underlying high-dimension feature space by adding selected feature centroids to the 2D scatter plots. This approach simultaneously visualizes the centers for the classes and the features on the same 2D scatter plot. Since classes are often imbalanced, we provide a method to balance class sizes. We present an automated framework that performs a grid search to find the optimal dimension reduction parameters, balances the class sizes, uses an ensemble approach to find the most important features, and adds class centroids and selected feature centroids to 2D dimension-reduced plots. This is especially useful when applied to complex, feature-rich biomedical data, as addition of feature centroids to 2D scatter plots serve as landmarks for the previously featureless dimension-reduced space. The utility of this approach is demonstrated by its application to seven classes of neurogenetic diseases with 31 defining phenotypic features.

关键词： Dimensionality reduction Three-dimensional displays Phenotypes Data visualization Data models Ensemble learning Bioinformatics Unsupervised learning Computational intelligence Diseases

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Detection of Various Dental Conditions on Dental Panoramic Radiography Using Faster R-CNN

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IEEE Access 2023年 11卷 127388-127401页

作者： Chen, Shih-Lun Chen, Tsung-Yi Mao, Yi-Cheng Lin, Szu-Yin Huang, Ya-Yun Chen, Chiung-An Lin, Yuan-Jin Chuang, Mian-Heng Abu, Patricia Angela R. Chung Yuan Christian University Department of Electronic Engineering Taoyuan320314 Taiwan Feng Chia University Department of Electronic Engineering Taichung407102 Taiwan Chang Gung Memorial Hospital Department of General Dentistry Taoyuan61363 Taiwan National Ilan University Department of Computer Science and Information Engineering Yilan26047 Taiwan Academy of Innovative Semiconductor and Sustainable Manufacturing Department of Program on Semiconductor Manufacturing Technology National Cheng Kung University Tainan717005 Taiwan Ming Chi University of Technology Department of Electrical Engineering New Taipei243303 Taiwan Ateneo de Manila University Department of Information Systems and Computer Science Quezon1108 Philippines

The dental panoramic radiograph (DPR) is a pivotal diagnostic tool in dentistry. However, despite the growing prevalence of artificial intelligence (AI) across various medical domains, manual methods remain the prevailing means of interpreting DPR images. This study aims to introduce an advanced identification system for detecting seven dental conditions in DPR images by utilizing Faster R-CNN. The primary objectives are to enhance dentists' efficiency and evaluate the performance of various CNN models as foundational training networks. This study contributes significantly to the field in several notable ways. Firstly, including a Butterworth filter in the training process yielded an approximately 7% enhancement in judgment accuracy. Secondly, the proposed enhancement technology tailored to different dental symptoms effectively bolstered the training model's accuracy. Consequently, all dental conditions attained an accuracy rate exceeding 95% in CNN analysis. These accuracy enhancements ranged from 1.34% to 13.24% compared to existing recognition technologies. Thirdly, this study pioneers the application of Faster R-CNN for identifying dental conditions, achieving an impressive accuracy rate of 94.18%. The outcomes of this study mark a substantial advancement compared to prior research and offer dentists a more efficient and convenient means of pre-diagnosing dental conditions. © 2013 IEEE.

关键词： Image segmentation

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Empowering Urban Accessibility: A Prototype System for People with Disability

Empowering Urban Accessibility: A Prototype System for Peopl...

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International Conference on Advanced Learning Technologies (ICALT)

作者： Arlley Dos Santos Costa Luis Carlos Costa Fonseca Sofiane Labidi Graduate Program in Computer and Systems Engineering State University of Maranhão – UEMA São Luís Brazil Bachelor of Science and Technology Program -BICT Federal University of Maranhão – UFMA São Luis Brazil

ISBN: (数字)9798350362053

ISBN: (纸本)9798350362060

This work demonstrates the development of a prototype system that could improve urban and digital accessibility for People with Disability - PwD. The research involves using an academic questionnaire to enable a wider perspective of the central subject and assessing the effectiveness of the proposed solution. The main goal is to help social integration and make the future solution implementable for smart cities through an experiment in an academic campus. The dissertation is related to technological and social issues that might be used as a resource by researchers, public or private bodies interested in more profound studies. The document recognizes the lack of studies on this subject, especially in Brazil because there are few available articles. The prototype system is designed to tackle the issues faced by persons with disability in urban settings through platforms, applications and mobile phones as it proposes a comprehensive set of solutions when addressing accessibility for PwDs. In turn, this research fosters knowledge advancements in the field of urban accessibility and provides vital recommendations for developing inclusive technologies and policies.

关键词： Smart cities Prototypes People with disabilities Mobile handsets

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Enhancement of Channel Capacity in 5G Ultra Dense Network-UDN 2

Enhancement of Channel Capacity in 5G Ultra Dense Network-UD...

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2nd International Conference on Edge Computing and Applications, ICECAA 2023

作者： Rastogi, Ritesh Shanthi, T. Kumar Naik, Pramod Sheela, M. Sahaya Mishra, A.K. Nandhini, T.J. Delhi India Paavai Engineering College Department of Ece Chennai India Dayananda Sagar University Departmeny of Computer Science Engineering Bangalore India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India Dhofar University Math Unit Foundation Program Salalah Oman Chennai India

ISBN: (纸本)9798350347579

A 5G ultra dense network architecture makes use of a high density of micro cell base stations to provide increased coverage, capacity, and performance for 5G communication systems. This is accomplished by the utilization of a very densely packed network. A 5G ultradense network is another name for this particular category of network. Ultradense networks are built to overcome the limitations of ordinary cellular networks. This is accomplished by increasing the number of base stations that are located inside a given area. This is performed by reducing the coverage area provided by each base station, which ultimately leads to an increase in the capacity of the entire network. The maximum data rate or capacity that may be obtained through a certain wireless channel is referred to as the 'channel capacity' in a 5G ultradense network, when the phrase 'channel capacity' is used. One possibility is that this represents the maximum quantity of data that can be transmitted across the channel. These criteria, which represent the capabilities of the channel, can be used to evaluate the performance of channels and equipment on 5G networks. This article presents for further research a model for improving the channel capacity of the 5G ultradense network. The model can be found at the end of the article. This change will result in an increase in both the usefulness of the channel and the amount of bandwidth that it consumes;both of these aspects will improve. The fact that it uses a very small quantity of energy and power in compared to other methods is the major trait that sets it apart from other methods. This technology is superior to others in terms of both the amount of data it can communicate and the amount of electricity it consumes in the process. © 2023 IEEE.

关键词： Energy efficiency

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Data Analytics and Visualization in Bimanual Rehabilitation Monitoring Systems: A User-Centered Design Approach to Healthcare Professionals Decision Support

Data Analytics and Visualization in Bimanual Rehabilitation ...

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International Conference on Electrical Engineering and Informatics (ICELTICs)

作者： Parkpoom Wisedsri Chutiporn Anutariya Aekavute Sujarae Roongtiwa Vachalathiti Sunee Bovonsunthonchai Computer Science Program School of Engineering and Technology Asian Institute of Technology Pathum Thani Thailand Punsarn Asia Co. Ltd Thailand Faculty of Physical Therapy Mahidol University Nakhon Pathom (MU) Thailand

ISBN: (数字)9798350366822

ISBN: (纸本)9798350366839

This study presents the design of a user-centered data visualization dashboard for stroke rehabilitation, which integrates the principles of visualization data analytics techniques in the field of healthcare. Addressing the complexities of visualizing for robotic bimanual rehabilitation, the design introduces novel methods to enhance data visualization, broadening monitoring capabilities, and improving the clarity of torque data. These enhancements lead to a clearer understanding of patient robot interactions. A prototype has been developed to visualize transparent torque data from a bimanual master slave robotic system, enabling healthcare professionals to monitor patient progress effectively. The dashboard features intuitive visual representations of master, slave, and assistive torques, simulating elbow joint movements through line and sunburst charts. Feedback from rehabilitation therapists during the design process ensures that the visualization approach is aligned with clinical needs. The findings suggest that the system can assist physiotherapists in devising personalized treatment strategies by providing actionable insights from the recorded data. However, additional research is needed to integrate real clinical data into the system for further enhancement and validation. This innovation has the potential to significantly improve stroke rehabilitation effectiveness and patient outcomes through a bimanual rehabilitation visualization and decision support system.

关键词： Data analysis Torque User centered design Data visualization Prototypes Medical services Stroke (medical condition) Main-secondary Monitoring Robots

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Exploring Tourist Feedback on Riau Attractions Through Indonesian Language YouTube Opinion Using Naïve Bayes Algorithm

Exploring Tourist Feedback on Riau Attractions Through Indon...

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2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications technology, IAICT 2023

作者： Kurniawan, Rahmad Iskandar, Iwan Lestari, Fitra Harpizon, Habibi Al Rasyid Husti, Ilyas Faculty of Mathematics and Natural Sciences Universitas Riau Department of Computer Science Pekanbaru Indonesia Universitas Islam Negeri Sultan Syarif Kasim Riau Department of Informatics Engineering Pekanbaru Indonesia Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Selangor Bangi Malaysia Graduate Program Universitas Islam Negeri Sultan Syarif Kasim Riau Pekanbaru Indonesia

ISBN: (纸本)9798350313635

YouTube is a widely-used platform in Indonesia, with 93.8% of its users. As such, it presents a valuable opportunity for marketing tourist destinations, particularly in Riau province, which aims to become Indonesia's top Halal travel destination. Tourism is a vital contributor to the economic growth of regions, and each province in Indonesia competes to promote its tourist attractions to attract more visitors every year. However, the large volume of data can challenge the manual analysis of feedback from YouTube's features, such as likes, dislikes, and comments. A literature review suggests that the Naive Bayes algorithm, which uses machine learning, is helpful for sentiment analysis. Therefore, this study aims to analyze public sentiment toward tourist destinations in Riau province by analyzing YouTube comments using the Naïve Bayes algorithm. The study used 1680 opinions collected from 10 YouTube videos showcasing tourist destinations in Riau. The Naive Bayes algorithm classified 60% of the comments as positive, 32% as neutral, and 8% as negative. The experimental results indicated an accuracy and precision of 73%, a recall of 94%, and an F-1 Score of 82%. The study used the word frequency technique to reveal that Riau could become a popular halal tourist destination based on several frequently occurring words in the comments. © 2023 IEEE.

关键词： Sentiment analysis

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