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Relations arising from a family of combinatorial numbers and Bernstein type basis functions

AIP Conference Proceedings 2018年第1期1978卷

作者： Irem Kucukoglu Yilmaz Simsek 1Department of Software Engineering Faculty of Engineering and Architecture Antalya Akev University Antalya Turkey 2Department of Mathematics Faculty of Science University of Akdeniz TR-07058 Antalya Turkey

The aim of this paper is to give some combinatorial sums, identities and relations related to a family of combinatorial numbers and the Bernstein type basis functions. With the help of generating functions for the combinatorial numbers from this aforementioned family, we give some functional equations. By using these functional equations, we obtain several relationships including these combinatorial numbers and the Bernstein type basis functions. Moreover, we provide not only some identities, but also applications including combinatorial sums, integrals, the combinatorial numbers, the extended Bersntein basis functions, and the beta function.

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Comparing the accuracy of machine learning models for accelerometer-based movement measurements

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Gait & Posture 2023年 106卷 S157-S158页

作者： Ozturk, Orhan Kaya, Derya Ozer Onan, Aytug University of İzmir Katip Celebi- Faculty of Health Science Physiotherapy and Rehabilitation İzmir Turkey University of İzmir Katip Celebi- Faculty of Engineering And Architecture Software Department İzmir Turkey

IntroductionMachine learning-based accelerometer data processing methods can potentially improve the classification of physical activity such as walking (brisk or normal), stair-up-down, etc. in adults [1,2]. Although simple machine learning methods (such as, decision trees, random forests) give good results in classifying basic functional movements [3], techniques such as bagging and boosting can further improve the accuracy and robustness of the classification, especially when dealing with more complex and diverse datasets or when the individual models have high variance. Ensemble methods can also help to reduce overfitting and improve generalization performance, by combining the strengths of multiple models and reducing the impact of individual weaknesses [4]. The purpose of this study was the evaluation of simple machine learning methods and their ensembles for the accelerometer-based movement measurements. Research questionWhat is the effect of the AdaBoost ensemble method on the classification accuracy of functional repetitive movements such as walking (brisk or normal), and stair-up-down obtained from the accelerometer? MethodsEleven participants (Age:28.90±2.53 years, BMI: 24.88±4.54 kg/m2) were included in the study. Participants wore an AX3 accelerometer (Axivity Ltd., United Kingdom) on their left wrist for obtaining data of functional repetitive movements (normal, side and brisk walking, standing, sitting and getting up, stair up and down). The data were taken of the vertical, mediolateral, and anteroposterior accelerations at 100 Hz sampling frequency (±8 g range). In this study, decision tree, random forest (RF), k-nearest neighbor, support vector machines, logistic regression, Naïve Bayes, and multi-layer perceptron (MLP) were trained with features extracted from the vector magnitude (VM) of the raw acceleration signal using 10 s non-overlapping windows. In addition, AdaBoost and majority voting ensembles were evaluated. ResultsRandom Forest and Multi

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OpenClinicalAI: enabling AI to diagnose diseases in real-world clinical settings

arXiv

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arXiv 2021年

作者： Huang, Yunyou Wang, Nana Tang, Suqin Ma, Li Hao, Tianshu Jiang, Zihan Zhang, Fan Kang, Guoxin Miao, Xiuxia Guan, Xianglong Zhang, Ruchang Zhang, Zhifei Zhan, Jianfeng Guangxi Key Lab of Multi-Source Information Mining & Security School of Computer Science and Engineering School of Software Guangxi Normal University Guilin China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China Guilin Medical University Guilin China Department of Physiology and Pathophysiology Capital Medical University Beijing China University of Chinese Academy of Sciences China International Open Benchmark Council

This paper quantitatively reveals the state-of-the-art and state-of-the-practice AI systems only achieve acceptable performance on the stringent conditions that all categories of subjects are known, which we call closed clinical settings, but fail to work in real-world clinical settings. Compared to the diagnosis task in the closed setting, real-world clinical settings pose severe challenges, and we must treat them differently. We build a clinical AI benchmark named Clinical AIBench to set up real-world clinical settings to facilitate researches. We propose an open, dynamic machine learning framework and develop an AI system named OpenClinicalAI to diagnose diseases in real-world clinical settings. The first versions of Clinical AIBench and OpenClinicalAI target Alzheimer’s disease. In the real-world clinical setting, OpenClinicalAI significantly outperforms the state-of-the-art AI system. In addition, OpenClinicalAI develops personalized diagnosis strategies to avoid unnecessary testing and seamlessly collaborates with clinicians. It is promising to be embedded in the current medical systems to improve medical services. © 2021, CC BY.

关键词： Diagnosis

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A Pattern Division Multiple Access Scheme with Low Complexity Iterative Receiver for 5G Wireless Communication Systems

A Pattern Division Multiple Access Scheme with Low Complexit...

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IEEE Vehicular Technology Conference

作者： Kai Zhang Jin Xu Changchuan Yin Chunyu Pan Weiqiang Tan Guixian Xu Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing 100876 P. R. China Zhengzhou University of Light Industry School of Computer and Communication Engineering Zhengzhou 450001 P. R. China Guangzhou University School of Computer Science and Educational Software Guangzhou 510006 P. R. China Aalborg University Department of Electronic Systems Aalborg 9400 Denmark

ISBN: (纸本)9781538663592;9781538663585

Non-orthogonal multiple access schemes with higher spectral efficiency and the capability of accessing more users than orthogonal multiple access (OMA) scheme is preferred for the fifth generation (5G) wireless networks. In this work, a non-orthogonal transmission scheme called pattern division multiple access (PDMA) is proposed for the 5G wireless communication systems. Two pattern matrices are proposed for 150% and 200% overloaded PDMA systems. Then, a low complexity symbol-wise belief propagation iterative detection and decoding (BPIDD) algorithm for multiple user detection is proposed. Numerical results and analysis provided by utilizing extrinsic information transfer chart show that the proposed scheme outperforms the traditional OMA systems significantly, and the performance of the proposed scheme is better than that of the existing schemes up to 1 dB. Finally, simulation results show that the proposed scheme is superior to the existing schemes and the proposed BPIDD algorithm is better than that of the BP algorithm over 0.5 dB.

关键词： 5G mobile communication iterative decoding matrix algebra multi-access systems multiuser detection Multi access systems matrix algebra Multiuser detection Iterative decoding multiple access Wireless communication systems Scheme iterative receiver spectral efficiency Information Transfer

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Image Segmentation Refinement Based on Region Expansion and Minor Contour Adjustments

SSRN

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SSRN 2024年

作者： Yan, Li-Yue Zhang, Xing Xiong, Si-Ting Song, Qing-Yun Zhang, De-Jin School of Architecture & Urban Planning Shenzhen University Shenzhen518061 China Guangdong Key Laboratory of Urban Spatial Information Engineering Shenzhen518061 China Key Laboratory of Greater Bay Area Geographic Environment Monitoring Ministry of Natural Resources Shenzhen518061 China Shenzhen Key Laboratory of Spatial Information Intelligent Perception and Service Shenzhen518061 China Guangdong Provincial Laboratory of Artificial Intelligence and Digital Economy Shenzhen518132 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518061 China

In high-precision image segmentation tasks, even slight deviations in the segmentation results can bring about significant consequences, especially in certain application areas such as in medical imaging and remote sensing image classification. The precision of segmentation has become the main factor limiting its development. Researchers typically refine image segmentation algorithms to enhance accuracy, but it is challenging for any improvement strategy to be applied effectively across different segmentation methods. It is also challenging to maintain consistent accuracy gains across different objects and image types. In order to solve this problem, in this article the further refinement of image segmentation results is proposed through the two-step refinement strategy of region expansion and minor contour adjustments. First, a dynamic gradient segmentation method dominated by closed contour position is proposed, which provides adaptive gradient constraints for the refinement algorithm. Then, region expansion is used to refine the target region iteratively with the help of color difference comparison and gradient information, while the minor contour adjustments are employed mainly to compare the intensity of gradients, assisted by regional colors, and finally adjust the contour position. This method takes into account both local region and pixel-level information, and adopts the form of dynamic judgment of adjacent region competition. The results show that the refined closed contour is closer to the ground truth. The deviation of contour turning points (corner points) has the most obvious improvement effect. The accuracy of image segmentation is improved. © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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Improved Qsofa Algorithm Based on PPG Wearable Device

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Journal of Physics: Conference Series 2021年第1期1848卷

作者： Yepeng Liu Xiaoxiao Yu Xin Luo Ziyu Liu Yu He College of Information Engineering Wuhan University of Technology Wuhan China College of Engineering and Architecture University College Dublin University College Dublin Belfield Dublin 4 College of Software Engineering Huazhong University of Science and Technology Wuhan China

This paper designs an improved Qsofa algorithm based on photoplethysmography measurement technology. The algorithm is mainly used to achieve accurate measurement of the subject's heart rate and blood pressure and a more refined Qsofa health score. In terms of health data processing, this paper uses a combination of data threshold and mean stabilization algorithms to significantly improve measurement accuracy. In terms of health analysis, this paper greatly reduces the difficulty of the GCS coma evaluation method in the traditional Qsofa algorithm, and at the same time makes the final score of the evaluation more detailed in the same level, so as to more accurately show the health status of the subjects.

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Assessment and Optimization of a Single Flash Geothermal System Recovered by a Trans-Critical Co2 Cycle Using Different Scenarios

SSRN

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SSRN 2023年

作者： Lamagna, Mario Aryanfar, Yashar Hoseinzadeh, Siamak Nastasi, Benedetto Garsia, Davide Astiaso Mohtaram, Soheil Sun, Hong Guang State Key Laboratory of Hydrology-Water Recourses and Hydraulic Engineering International Center for Simulation Software in Engineering and Sciences College of Mechanics and Materials Hohai University Jiangsu Nanjing210098 China Universidad Autónoma de Ciudad Juárez Mexico Department of Planning Design and Technology of Architecture Sapienza University of Rome Rome00196 Italy Department of Earth Sciences and Forecasting Research Center Prevention and Control of Geological Risks China Department of Earth Sciences and Forecasting Research Center Prevention and Control of Geological Risks China School of Energy and Power Engineering University of Shanghai for Science and Technology Shanghai200093 China

Globally, the use of renewable energy, particularly geothermal energy, is rising quickly. Geothermal cycles' low efficiency has repeatedly shown how crucial it is to recover heat lost during these cycles. This study suggests a combined power generation cycle replicating using the EES software environment that combines a single flash cycle with a trans-critical carbon dioxide cycle. The findings demonstrate that, in comparison to the BASIC single flash cycle, the design characteristics of the proposed system are greatly improved. The suggested strategy is then enhanced by employing the genetic algorithm, the Nelder-Mead Simplex method, and the direct algorithm. Separator pressure, steam turbine outlet pressure, and carbon dioxide turbine inlet pressure are three assumed variable parameters, and exergy efficiency is the target parameter. In the default operating mode, the system exergy efficiency is 32.46%, increasing to 39.21% using the genetic algorithm and 36.16% using the Nelder-Mead method and 38.82% using the direct algorithm. © 2023, The Authors. All rights reserved.

关键词： Genetic algorithms

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Greencoin: prototype of a mobile application facilitating and evidencing pro-environmental behavior of citizens

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Procedia Computer Science 2021年 192卷 2668-2677页

作者： Kacper Radziszewski Helena Anacka Hanna Obracht-Prondzyńska Dorota Tomczak Kacper Wereszko Paweł Weichbroth Gdańsk University of Technology Faculty of Architecture Deparment of Visual Arts Gabriela Narutowicza 11/12 Gdańsk 80-233 Poland Gdańsk University of Technology Faculty of Management and Economics Department of Economic Sciences Traugutta 79 Gdańsk 80-233 Poland Gdańsk University of Technology Faculty of Architecture Department of Urban Design and Regional Planning Gabriela Narutowicza 11/12 Gdańsk 80-233 Poland Gdańsk University of Technology Faculty of Electronics Telecommunications and Informatics Gabriela Narutowicza 11/12 Gdańsk 80-233 Poland Gdańsk University of Technology Faculty of Electronics Telecommunications and Informatics Department of Software Engineering Gabriela Narutowicza 11/12 Gdańsk 80-233 Poland

Among many global challenges, climate change is one of the biggest challenges of our times. While it is one of the most devastating problems humanity has ever faced, one question naturally arises: can individuals make a difference? We believe that everyone can contribute and make a difference to the community and lives of others. However, there is still a lack of effective strategies to promote and facilitate pro-environmental behavior of individuals. To fill this gap, in this paper, we introduce and discuss the Greencoin mobile application prototype. The app is built on existing intelligent data-driven technologies, including supervised and unsupervised learning techniques. Since its end-users will mostly concern the city dwellers, the project falls into the scope of the ongoing research in the area of smart city applications. Nevertheless, the application is still in the design phase, we believe it is a good starting point to spark discussion on its further directions of development, as well as to draw the attention of both national and international audiences to the issues raised.

关键词： Digital Innovation Mobile Prototype Smart City

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Experimental verification of latticed acoustic metamaterials with pentamode to bandgap characteristics

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The European Physical Journal. B 2024年第12期97卷 192-192页

作者： Feilong Gong Qi Li Zifei Xiao Song Liu School of Naval Architecture and Ocean Engineering Dalian Maritime University 116026 Dalian China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment 116024 Dalian China School of Naval Architecture and Ocean Engineering Dalian University of Technology 116024 Dalian China

Pentamode and bandgap characteristics of metamaterials are of great significance to the control of elastic wave propagation by acoustic metamaterials. Pentamode metamaterials are artificially designed solid structures that exhibit fluid-like behavior. The bandgap characteristic of metamaterials effectively hinders the propagation of elastic waves. A latticed metamaterial with pentamode characteristics is proposed, achieving bandgap features by altering the positions of nodes between arms in the unit structures. This study aims to experimentally verify the pentamode and bandgap characteristics of acoustic metamaterials. Finite element analysis using COMSOL Multiphysics and underwater experiments with three models theoretically and experimentally validate the ability of latticed metamaterials to control elastic wave propagation under various parameters. By examining the band structure, the propagation of acoustic waves within the pentamode domain (10–20 kHz) for pentamode model and bandgap domain (5–10 kHz) for bandgap models are assessed. The experimental results agree with the theoretical simulations. The pentamode and bandgap characteristics of the latticed metamaterials have a broad development prospect in acoustic detection.

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Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 2981卷 V-VI页

作者： Müller-Schloer, Christian Ungerer, Theo Bauer, Bernhard University of Hannover Institute of Systems Engineering System and Computer Architecture - SRA Appelstr. 4 Hannover Germany University of Augsburg Institute of Informatics Augsburg Germany University of Augsburg Department of Software Engineering and Programming Languages Augsburg Germany

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