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Explainable ai-driven evaluation of plant protein rheology using tree-based and Gaussian process machine learning models

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ain Shams engineering Journal 2025年第9期16卷

作者： Mustafa Tahsin Yilmaz Salman Badurayq Kemal Polat Ahmad H. Milyani Abdulaziz S. Alkabaa Osman Gul Furkan Turker Saricaoglu Department of Industrial Engineering Faculty of Engineering King Abdulaziz University Jeddah Saudi Arabia Center of Research Excellence in Artificial Intelligence and Data Science (AIADS) King Abdulaziz University Jeddah Saudi Arabia Production Chief at Pladis Global Phase 3 Industrial Area Jeddah Saudi Arabia Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah Saudi Arabia Center of Excellence in Intelligent Engineering Systems (CEIES) King Abdulaziz University Jeddah Saudi Arabia Department of Food Engineering Faculty of Engineering and Architecture Kastamonu University Kastamonu Turkey Department of Food Engineering Faculty of Engineering and Natural Science Bursa Technical University Bursa Turkey Faculty of Engineering Department of Electrical and Electronics Engineering Bolu Abant Izzet Baysal University Bolu TR 14280 Turkey

In this study, we conducted a comparative analysis of the explainability of Decision Tree Regressor (DTR) and Gaussian Process Regressor (GPR) models in predicting the shear stress and viscosity of sesame protein isolate (SPI) systems, employing explainable machine learning (EML) techniques to elucidate complex, nonlinear relationships among processing parameters. SPI samples were processed across pressure levels ranging from 0 to 100 MPa and ion concentration (IC) values from 0 to 200 mM. DTR model accurately predicted shear stress ( R 2 = 0.999), while a GPR model achieved high performance for viscosity prediction ( R 2 = 0.9925). Formally, the modeling task is framed as learning a predicting mapping function f : R p → R , where x ∈ R p denotes the vector of predictors (pressure, IC, shear rate) and y ∈ R is the target variable (shear stress or viscosity), by minimizing a loss function such as mean squared error. Interpretation of model predictions using SHapley Additive exPlanations (SHAP), permutation importance, and partial dependence analysis revealed that pressure and IC are the most influential factors affecting shear stress and viscosity, with pressure inducing protein conformational changes that impact rheological properties. The shear rate exhibited a lesser direct impact within the systems examined. Partial Dependence Plots (PDPs) from the DTR model revealed strong, nearly linear positive relationships between pressure and shear stress, while the GPR model depicted more nuanced responses, highlighting the models’ differing sensitivities. Variance-Based Sensitivity Indices (VBSIs) further quantified these influences, with pressure and IC showing higher sensitivity scores in the DTR model compared to the GPR model. Permutation importance and SHAP interaction analyses corroborated these results, emphasizing the dominant role of pressure and IC, both independently and interactively, in determining shear stress. In contrast, viscosity predictions were influ

关键词： Explainable artificial intelligence Sesame protein isolates Steady shear rheology Tree-based machine learning models Gaussian Process regressor

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Automatic Assessment System of Pulse Diagnosis for Treatment Effect Evaluation 8

Automatic Assessment System of Pulse Diagnosis for Treatment...

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8th International Conference on Innovation, Communication and engineering, ICICE 2019

作者： Shen, Kai-Ming Chang, Che-Wei School of Electrical and Computer Engineering College of Engineering Chang Gung University Department of Computer Science and Information Engineering Tao-Yuan Taiwan Department of Physical Medicine and Rehabilitation Chang Gung Memorial Hospital Tao-Yuan Taiwan Ai Innovation Research Center Chang Gung University TaoYuan Taiwan

ISBN: (纸本)9781728158396

Pulse Diagnosis (PD) is a well-established diagnostic technique used in Traditional Chinese Medicine (TCM). The positions for PD are the radial arteries in the left and right wrists, and the pulse assessment is done by placing index, middle, and ring fingers on each wrist. The pulse of patients is then measured in the superficial, middle, and deep levels by TCM doctors to obtain more information regarding energy or Qi imbalance of the patients. For modern medical researches, PD is also used for indicating some status of patients. However, it is a challenging issue for all medical staff to properly assess the pulse of various patients. Therefore, this work proposes a systematic scheme to measure patient pulse by Photoplethysmography (PPG) sensors. An evaluation framework of some treatments, e.g., acupuncture therapy, is then built on top of the PPG sensing system with machine learning solutions. In our implementation, sensor data will be collected and transferred from Arduino platforms to our server for the PD assessment. The effect of the evaluated treatments will be estimated by the analysis of the PD results with machine learning supports. The major performance index is on the accuracy of the assessment for the treatments. © 2019 IEEE.

关键词： Machine learning

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The Ridership Analysis on Inter-County/City Service for the Case Study of Taichung City Bus System 23rd

The Ridership Analysis on Inter-County/City Service for the ...

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23rd International computer Symposium, ICS 2018

作者： Ho, Cheng-Yuan Chiu, I-Hsuan Department of Computer Science and Information Engineering Asia University Taichung City Taiwan Big Data Research Center Asia University Taichung City Taiwan Taichung City Smart Transportation Big Data Research Center Asia University Taichung City Taiwan Department of Civil Engineering National Chiao Tung University Hsinchu City Taiwan

ISBN: (纸本)9789811391897

In order to find passengers’ behaviors when the passengers take buses, more than 82 million records of electronic ticket transactions of Taichung City Bus in 2015 and 8 inter-county/city bus routers are analyzed in this article. There are three statistical/analytic results. First, about 5.26 million electronic ticket users received benefits from Taichung City Government’s policy;however, less than 0.5% users still used cash. The situations of 8 inter-county/city bus services in adjacent counties were little similar to that of Taichung City. Second, route 208 was the major route took by most people between Taichung City and Miaoli County among the routes supported by Taichung City Government. Routes 108 and 101 were the major routes connecting Nantou County and Taichung City, and Changhua County and Taichung City, respectively. Finally, in three adjacent counties, the names of top 5 bus stops for each county are almost same, but the order of top 5 bus stops for each county are quite different. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Big data

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research on Passenger Carrying Capacity of Taichung City Bus with Big data of Electronic Ticket Transactions: A Case Study of Route 151 23rd

Research on Passenger Carrying Capacity of Taichung City Bus...

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23rd International computer Symposium, ICS 2018

ISBN: (纸本)9789811391897

In order to find passengers’ behaviors when the passengers take buses, 456 thousand and 82 million records of electronic ticket transactions of route 151 and Taichung City Bus in 2015 are respectively analyzed in this article. There are three statistical/analytic results. First, about 5.26 million electronic ticket users received benefits from Taichung City Government’s policy for a free bus ride within 10 km with an electronic ticket;however, less than 0.5% users still used cash. Second, The passengers usually got on and off route 151 at THSR Taichung Station no matter which direction. Other bus stops for passengers usually getting on and off were T.P.C.C., Wufeng Agr. Ind. Senior High School, Wufeng, and Wufeng Post Office. Finally, on Friday and the day before holidays, many passengers changed their behaviors to take route 151 from Wufeng District to THSR Taichung Station. This change was that the passengers took another bus route to the station near the start station of route 151 to increase the probability to get on the route 151. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Big data

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The Dynamic Sensorium competition for predicting large-scale mouse visual cortex activity from videos

arXiv

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arXiv 2023年

作者： Turishcheva, Polina Fahey, Paul G. Hansel, Laura Froebe, Rachel Ponder, Kayla Vystrčilová, Michaela Willeke, Konstantin F. Bashiri, Mohammad Wang, Eric Ding, Zhiwei Tolias, Andreas S. Sinz, Fabian H. Ecker, Alexander S. Qiur, Yongrong Institute of Computer Science and Campus Institute Data Science University of Göttingen Germany Department of Neuroscience Baylor College of Medicine HoustonTX United States Center for Neuroscience and Artificial Intelligence Baylor College of Medicine HoustonTX United States Department of Ophthalmology Byers Eye Institute Stanford University School of Medicine StanfordCA United States Stanford Bio-X Stanford University StanfordCA United States Wu Tsai Neurosciences Institute Stanford University StanfordCA United States International Max Planck Research School for Intelligent Systems University of Tübingen Germany Institute for Bioinformatics and Medical Informatics University of Tübingen Germany Department of Electrical Engineering Stanford University StanfordCA United States Max Planck Institute for Dynamics and Self-Organization Göttingen Germany

Understanding how biological visual systems process information is challenging due to the complex nonlinear relationship between neuronal responses and high-dimensional visual input. Artificial neural networks have already improved our understanding of this system by allowing computational neuroscientists to create predictive models and bridge biological and machine vision. During the Sensorium 2022 competition, we introduced benchmarks for vision models with static input (i.e. images). However, animals operate and excel in dynamic environments, making it crucial to study and understand how the brain functions under these conditions. Moreover, many biological theories, such as predictive coding, suggest that previous input is crucial for current input processing. Currently, there is no standardized benchmark to identify state-of-the-art dynamic models of the mouse visual system. To address this gap, we propose the Sensorium 2023 Benchmark Competition with dynamic input (https://***/). This competition includes the collection of a new large-scale dataset from the primary visual cortex of ten mice, containing responses from over 78,000 neurons to over 2 hours of dynamic stimuli per neuron. Participants in the main benchmark track will compete to identify the best predictive models of neuronal responses for dynamic input (i.e. video). We will also host a bonus track in which submission performance will be evaluated on out-of-domain input, using withheld neuronal responses to dynamic input stimuli whose statistics differ from the training set. Both tracks will offer behavioral data along with video stimuli. As before, we will provide code, tutorials, and strong pre-trained baseline models to encourage participation. We hope this competition will continue to strengthen the accompanying Sensorium benchmarks collection as a standard tool to measure progress in large-scale neural system identification models of the entire mouse visual hierarchy and

关键词： Mammals

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A large deviation principle for block models

arXiv

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arXiv 2020年

作者： Borgs, Christian Chayes, Jennifer Gaudio, Julia Petti, Samantha Sen, Subhabrata University of California Berkeley United States Massachusetts Institute of Technology United States Harvard University United States Berkeley AI Research Group Department of Electrical Engineering and Computer Science Department of Electrical Engineering and Computer Science Department of Mathematics Department of Statistics School of Information Department of Mathematics NSF-Simons Center for Mathematical and Statistical Analysis of Biology Department of Statistics

We initiate a study of large deviations for block model random graphs in the dense regime. Following [14], we establish an LDP for dense block models, viewed as random graphons. As an application of our result, we study upper tail large deviations for homomorphism densities of regular graphs. We identify the existence of a "symmetric" phase, where the graph, conditioned on the rare event, looks like a block model with the same block sizes as the generating graphon. In specific examples, we also identify the existence of a "symmetry breaking" regime, where the conditional structure is not a block model with compatible dimensions. This identifies a "reentrant phase transition" phenomenon for this problem—analogous to one established for Erdős–Rényi random graphs [13, 14]. Finally, extending the analysis of [33], we identify the precise boundary between the symmetry and symmetry breaking regime for homomorphism densities of regular graphs and the operator norm on Erdős–Rényi bipartite *** Codes 60F10, 05C80, 60C05 Copyright © 2020, The Authors. All rights reserved.

关键词： Graphic methods

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NTIRE 2023 Challenge on Light Field Image Super-Resolution: dataset, Methods and Results

arXiv

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arXiv 2023年

作者： Wang, Yingqian Wang, Longguang Liang, Zhengyu Yang, Jungang Timofte, Radu Guo, Yulan Jin, Kai Wei, Zeqiang Yang, Angulia Guo, Sha Gao, Mingzhi Zhou, Xiuzhuang Van Duong, Vinh Huu, Thuc Nguyen Yim, Jonghoon Jeon, Byeungwoo Liu, Yutong Cheng, Zhen Xiao, Zeyu Xu, Ruikang Xiong, Zhiwei Liu, Gaosheng Jin, Manchang Yue, Huanjing Yang, Jingyu Gao, Chen Zhang, Shuo Chang, Song Lin, Youfang Chao, Wentao Wang, Xuechun Wang, Guanghui Duan, Fuqing Xia, Wang Wang, Yan Xia, Peiqi Wang, Shunzhou Lu, Yao Cong, Ruixuan Sheng, Hao Yang, Da Chen, Rongshan Wang, Sizhe Cui, Zhenglong Chen, Yilei Lu, Yongjie Cai, Dongjun An, Ping Salem, Ahmed Ibrahem, Hatem Yagoub, Bilel Kang, Hyun-Soo Zeng, Zekai Wu, Heng National University of Defense Technology China Aviation University of Air Force China University of Würzburg Germany ETH Zürich Switzerland The Shenzhen Campus of Sun Yat-Sen University Sun Yat-Sen University China Bigo Technology Pte. Ltd Singapore Smart Medical Innovation Lab Beijing University of Posts and Telecommunications China Global Explorer Ltd. Suzhou China National Engineering Research Center of Visual Technology School of Computer Science Peking University China School of Artificial Intelligence Beijing University of Posts and Telecommunications China Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of University of Science and Technology of China China School of Electrical and Information Engineering Tianjin University China Beijing Key Lab of Traffic Data Analysis and Mining School of Computer and Information Technology Beijing Jiaotong University China Beijing Normal University China Toronto Metropolitan University Canada Beijing Institute of Technology China Shenzhen MSU-BIT University China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University China Beihang Hangzhou Innovation Institute Yuhang China Faculty of Applied Sciences Macao Polytechnic University China School of Communication and Information Engineering Shanghai University China School of Information and Communication Engineering Chungbuk National University Korea Republic of Guangdong University of Technology China

In this report, we summarize the first NTIRE challenge on light field (LF) image super-resolution (SR), which aims at super-resolving LF images under the standard bicubic degradation with a magnification factor of 4. This challenge develops a new LF dataset called NTIRE-2023 for validation and test, and provides a toolbox called BasicLFSR to facilitate model development. Compared with single image SR, the major challenge of LF image SR lies in how to exploit complementary angular information from plenty of views with varying disparities. In total, 148 participants have registered the challenge, and 11 teams have successfully submitted results with PSNR scores higher than the baseline method LF-InterNet [1]. These newly developed methods have set new state-of-the-art in LF image SR, e.g., the winning method achieves around 1 dB PSNR improvement over the existing state-of-the-art method DistgSSR [2]. We report the solutions proposed by the participants, and summarize their common trends and useful tricks. We hope this challenge can stimulate future research and inspire new ideas in LF image SR. © 2023, CC BY-SA.

关键词： Image enhancement

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LCBNI: Link completion bipartite network inference for predicting new lncRNA-miRNA interactions

LCBNI: Link completion bipartite network inference for predi...

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2018 IEEE International Conference of Safety Produce Informatization, IICSPI 2018

作者： Yu, Zhenkun Zhu, Fuxi Tianl, Gang Wang, Hao School of Computer Science Wuhan University Wuhan430072 China AI Application Research Center Wuhan College Wuhan Hubei430211 China State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil Mechanics Chinese Academy of Sciences Wuhan430071 China

ISBN: (纸本)9781538655139

LncRNAs and miRNAs are two different kinds of non-coding RNAs and are both important for human in the field of health and disease. LncRNAs can interact with miRNAs, and the interactions play key roles in gene regulatory networks. Predicting IncRNA-miRNA interactions is an urgent and significant task and can help to explore the mechanism of involved complicated diseases, but very few computational methods are developed. In this paper, we introduce a computational method named link completion bipartite network inference (LCBNI) to predict the potential interactions between IncRNAs and miRNAs. LCBNI formulates the observed IncRNA-miRNA interactions as a bipartite network. Considering that there is no any known interaction for new IncRNAs or miRNAs, LCBNI calculates the sequence similarity and utilizes weighted nearest neighbor interaction information to construct new interaction scores for these IncRNAs and miRNAs. Then, we implement a resource allocation algorithm on the bipartite network to predict IncRNA-miRNA interactions. The experimental results demonstrate that LCBNI can effectively predict IncRNA-miRNA interactions with higher accuracy compared with other state-of-the-art methods and network-based methods, including random walk with restart (RWR), IncRNA-based collaborative filtering (LncCF) and miRNA-based collaborative filtering (MiCF). Furthermore, case studies are performed to demonstrate the prediction capability of LCBNI using real data. © 2018 IEEE.

关键词： Collaborative filtering

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A Novel Robust Visible Light Positioning Based on Sparsity-Adaptive Compressed Sensing

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Journal of Lightwave Technology 2025年

作者： Xu, Shiwu Wu, Yi Xing, Song Zhang, Longteng Fujian Normal University Concord University College Fuzhou350117 China Fujian Normal University Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application Fuzhou350117 China California State University Department of Information Systems Los AngelesCA90032 United States Fujian University of Technology School of Computer Science and Mathematics Fuzhou350118 China

The fingerprint-based visible light positioning (VLP) method offers high-precision indoor positioning with centimeter-level accuracy, making it well-suited for applications like robot navigation. However, the sensitivity of photodiodes (PDs) to natural light compromises the system's robustness. To address this challenge, we construct a robust received signal strength (RSS) database that leverages the properties of pulse width modulation (PWM) technology to minimize interference from natural light. This robust RSS database serves as the foundation for a novel, low-complexity, sparsity-adaptive compressed sensing (CS) algorithm, which enables accurate signal reconstruction without requiring prior knowledge of sparsity. Experimental results show that the proposed VLP system effectively mitigates the impact of natural light and maintains consistent positioning performance across varying natural lighting conditions. With a grid spacing of 20 cm, the proposed RSS database construction method achieves an average positioning error (APE) of 1.36 cm in VLP, marking a 75.54% reduction compared to the traditional RSS database construction method. Furthermore, the proposed VLP system maintains an APE of 2.15 cm even at a 40 cm grid spacing. This demonstrates that our system achieves excellent positioning accuracy while maintaining low computational and storage complexity. © 1983-2012 IEEE.

关键词： Image reconstruction

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Magnetic and levitation properties of YBCO/polymer composite drop-casting films

Next Materials

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Next Materials 2025年 8卷

作者： Beatriz Lucas Miguel Brito Canan Aksoy Bakiye Cakir Elvan Coşkun Ali Gencer Anabela Pronto Isabel Ferreira CENIMAT|i3N Department of Materials Science School of Science and Technology NOVA University Lisbon Caparica Portugal Electrical and Computer Engineering Department School of Science and Technology NOVA University Lisbon Caparica Portugal Electronics and Communication Engineering Faculty of Technology Karadeniz Technical University Trabzon 61830 Turkiye Vocational School of Health Services Artvin Çoruh University Artvin 08000 Turkiye Ankara University Superconductor Technologies Application and Research Center Gölbaşı Ankara Turkiye Ankara University Faculty of Sciences Physics Department Ankara 06100 Turkiye Center of Technology and Systems CTS/UNINOVA School of Science and Technology NOVA University Lisbon Caparica Portugal

Superconducting materials have been extensively studied for various applications, with YBCO alloys among the most researched and widely applied. This paper investigates the feasibility of using YBCO powder-based inks to produce cost-effective films with magnetic properties. Our studies demonstrate that levitation in liquid nitrogen is consistently observed in all fabricated films, regardless of ink composition or application method. Both drop-casting and spray-coating techniques were successfully employed to create levitating films. Additionally, various substrates—including aluminum foil (with and without adhesive), plastic foil, Teflon, and paper—were evaluated, with no significant impact on levitation performance. The levitation height was also compared to samples without a substrate. Depending on the binder, the resulting films exhibit rigidity or flexibility while maintaining their levitation capabilities even after multiple bending cycles. However, film conductivity is influenced by the binder type and concentration, which also affects the critical current density. A film with a thickness of 300 μm demonstrated a Jc of 2 kA/cm² at 65 K and zero magnetic field.

关键词： YBCO superconductor powders Polymers superconductor hybrid materials Selfsustained drop-casting films Levitation and magnetic properties Surface and chemical analysis

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