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A Hybrid Parallel Strategy for Isogeometric Topology Optimization via CPU/GPU Heterogeneous Computing

computer Modeling in engineering & sciences 2024年第2期138卷 1103-1137页

作者： Zhaohui Xia Baichuan Gao Chen Yu Haotian Han Haobo Zhang Shuting Wang The State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan430074China School of Mathematics and Computer Science Wuhan Polytechnic UniversityWuhan430048China School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan430074China

This paper aims to solve large-scale and complex isogeometric topology optimization problems that consumesignificant computational resources. A novel isogeometric topology optimization method with a hybrid parallelstrategy of CPU/GPU is proposed, while the hybrid parallel strategies for stiffness matrix assembly, equationsolving, sensitivity analysis, and design variable update are discussed in detail. To ensure the high efficiency ofCPU/GPU computing, a workload balancing strategy is presented for optimally distributing the workload betweenCPU and GPU. To illustrate the advantages of the proposedmethod, three benchmark examples are tested to verifythe hybrid parallel strategy in this paper. The results show that the efficiency of the hybrid method is faster thanserial CPU and parallel GPU, while the speedups can be up to two orders of magnitude.

关键词： Topology optimization high-efficiency isogeometric analysis CPU/GPU parallel computing hybrid OpenMPCUDA

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Enhancing Evapotranspiration Estimation: A Bibliometric and Systematic Review of Hybrid Neural Networks in Water Resource Management

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computer Modeling in engineering & sciences 2025年第2期142卷 1109-1154页

作者： Moein Tosan Mohammad Reza Gharib Nasrin Fathollahzadeh Attar Ali Maroosi Department of Water Science and Engineering Faculty of AgricultureUniversity of BirjandBirjand***Iran Department of Mechanical Engineering University of Torbat HeydariehTorbat Heydarieh***Iran Department of Water Engineering Faculty of AgricultureUrmia UniversityUrmia***Iran Department of Computer Engineering University of Torbat HeydariehTorbat Heydarieh***Iran

Accurate estimation of evapotranspiration(ET)is crucial for efficient water resource management,particularly in the face of climate change and increasing water *** study performs a bibliometric analysis of 352 articles and a systematic review of 35 peer-reviewed papers,selected according to PRISMA guidelines,to evaluate the performance of Hybrid Artificial Neural Networks(HANNs)in ET *** findings demonstrate that HANNs,particularly those combining Multilayer Perceptrons(MLPs),Recurrent Neural Networks(RNNs),and Convolutional Neural Networks(CNNs),are highly effective in capturing the complex nonlinear relationships and tem-poral dependencies characteristic of hydrological *** hybrid models,often integrated with optimization algorithms and fuzzy logic frameworks,significantly improve the predictive accuracy and generalization capabilities of ET *** growing adoption of advanced evaluation metrics,such as Kling-Gupta Efficiency(KGE)and Taylor Diagrams,highlights the increasing demand for more robust performance assessments beyond traditional *** the promising results,challenges remain,particularly regarding model interpretability,computational efficiency,and data *** research should prioritize the integration of interpretability techniques,such as attention mechanisms,Local Interpretable Model-Agnostic Explanations(LIME),and feature importance analysis,to enhance model transparency and foster stakeholder ***,improving HANN models’scalability and computational efficiency is crucial,especially for large-scale,real-world *** such as transfer learning,parallel processing,and hyperparameter optimization will be essential in overcoming these *** study underscores the transformative potential of HANN models for precise ET estimation,particularly in water-scarce and climate-vulnerable *** integrating CNNs for automatic feature extraction and leveraging hybr

关键词： Artificial neural networks bibliometric analysis evapotranspiration hybrid models research trends systematic literature review water resources management

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A Model Driven Framework Enabling the Development of Standardized Text-Free User Interface for Smartphones 21

A Model Driven Framework Enabling the Development of Standar...

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21st International Bhurban Conference on Applied sciences and Technology, IBCAST 2024

作者： Rasheed, Uzair Khalid, Sadia Mehmood, Rabia Ahmad, Muhammad Muneer, Mishal College of Electrical and Mechanical Engineering NUST Department of Computer and Software Engineering Islamabad Pakistan Lahore College for Women University Department of Computer Science Lahore Pakistan International Univesity of Rostock Department of Computer science Germany

ISBN: (纸本)9798331516680

Smartphones offer a wide range of applications globally, and usability is a key factor in their quality. Human-computer Interaction (HCI) continuously evolves to enhance usability by improving user interface (UI) components. However, most UI trends are designed for literate users, neglecting a significant portion of the population who cannot read or write. These users often rely on others for assistance with smartphone applications, and text-based UIs hinder their learning and usage, reducing overall usability. This research addresses the limitations of text-based standards by introducing a standardized framework for developing text-free user interfaces for smartphones. The framework utilizes static and dynamic images instead of text to convey widget or button functions, aiming to enhance usability for illiterate users, including preschoolers. Developed with Obeo Designer and Sirius, the framework's Platform Independent Metamodel (PIM) was validated through case studies representing the target user groups. Future work involves Model to Text (M2T) transformation, and results show the framework's potential for automating applications with text-free UIs. © 2024 IEEE.

关键词： Smartphones

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Drug Review Classification by Using Sentiment Analysis 3rd

Drug Review Classification by Using Sentiment Analysis

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3rd International Conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Dasari, Krishna Kumar Bhaskar, Nuthanakanti Bagam, Laxmaiah Madhusudhan, Mudimela Santhuja, Pandu Avala, Raji Reddy Department of Computer Science and Engineering CMR Technical Campus Hyderabad India Department of Mechanical Engineering CMR Technical Campus Hyderabad India

ISBN: (纸本)9789819783540

The drugs sentiment analysis has grown significantly in importance in the modern day since categorizing medications based on their efficacy by examining user evaluations can help possible future customers in learning more and making better selections about certain drugs. Using social media, blogs, and other sources, sentiment analysis is a popular approach for obtaining opinions from a large number of people. In addition to a lack of accessibility, many people started using medications on their own without the necessary consultations it increased the severity of the health issue. Numerous fields have found applications for machine learning, and creative work for automation is increasing. The information intends to show a medication recommendation method that could significantly decrease the need for specialists. Implementing machine learning methods, such as light gradient boosting machine (LGBM) K-nearest neighbours (KNN), CAT (computer-aided translation) boost, decision tree (DT), and, in order to assess the information and create a model that conducts sentiment classification. Measurements for precision, accuracy, recall, and F1 score were utilized to evaluate the attitudes that were shown. As a consequence, the outcomes demonstrate that the classifier outperforms other approaches. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Nearest neighbor search

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Enhancing sound pressure output in graphene-based hybrid bone conduction hearing aids through electromagnetic and electrostatic integration

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Nano Research 2025年第4期18卷 425-434页

作者： Dong-Kwan Lee Hyunwoo Baek Byung-Ho Kang § Jongchan Yoo Kun-Woo Nam Sang Hyun Lee Illsoo Sohn Eunjung Han June Choi Sung-Hoon Park Department of Mechanical Engineering Soongsil UniversitySeoul 06978Republic of Korea Department of Otorhinolaryngology-Head and Neck Surgery Korea University College of MedicineAnsan HospitalAnsan 15355Republic of Korea School of Electrical Engineering Korea UniversitySeoul 02841Republic of Korea Department of Computer Science and Engineering Seoul National University of Science and TechnologySeoul 01811Republic of Korea

Bone conduction hearing aids(BCHA)actively serve patients with conductive hearing loss or external auditory canal problems,including auditory canal atresia,ossicular dislocation,*** are typically categorized into surgically implanted devices,embedded directly into the skull,and adhesive devices,which transmit sound through the *** latter are advantageous for being noninvasive and suitable for children under ***,adhesive devices,due to their sound transmission method,require enhanced sound output performance compared to implanted ***,known for its low mass density yet excellent mechanical and electrical properties,finds application in various electronic ***,it serves as a diaphragm in electroacoustic transducers,enabling stable vibrations across broad frequency *** electroacoustic transducers of BCHA are typically driven by electromagnetic methods,which may be effective in low-frequency ranges but not in high-frequency *** study successfully introduced a hybrid approach that combines the complementary advantages of both electromagnetic and electrostatic modes by utilizing a graphene sheet as the diaphragm for a hybrid graphene *** electrostatic mode,which performs better in highfrequency ranges compared to the electromagnetic mode,was implemented in this hybrid *** to the measured frequency response data,the hybrid mode showed up to an 11 dB improvement compared to the electromagnetic mode and up to a 21 dB improvement compared to the electrostatic mode,exhibiting a relatively flat shape over a wide frequency ***,the device’s effectiveness as a BCHA is confirmed through experiments on rabbits,showcasing its potential in auditory aid advancement.

关键词： graphene bone conduction hearing aid loudspeaker frequency response

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Corrosion Testing of Carbon Steel and 13Cr Casing Materials in Simulated Superhot Deep Geothermal Well Environment

Corrosion Testing of Carbon Steel and 13Cr Casing Materials ...

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Association for Materials Protection and Performance Annual Conference and Expo 2024

作者： Karlsdottir, Sigrun Nanna Straume, Erlend Boakye, Gifty Oppong Pórhallsson, Andri Ísak Práinsdóttir, María Ýr Faculty of Computer Science Industrial and Mechanical Engineering University of Iceland Hjardarhagi 2-6 Reykjavik Iceland

Major challenges are encountered in the design and construction of deep superhot (>300°C) geothermal wells due to higher temperatures and pressure, and increased corrosiveness of the geothermal fluid. The corrosiveness of the geothermal fluid is due to the chemical composition which includes corrosive gases such as HCl, H2S and CO2. In this study L80-type 1 carbon steel and L80-13Cr stainless steel API casing materials were tested in a simulated superhot geothermal well environment at 350°C in water with Cl, H2S and CO2 for 168 hrs. in both vapor and liquid phases in high temperature and high pressure (HTHP) autoclave to investigate their corrosion behavior. The results showed that both API casing materials, L80-type 1 and L80-13Cr, were prone to corrosion attack in the simulated superhot deep geothermal well environment. The L80 grade Type 1 carbon steel tested in the liquid phase exhibited the highest corrosion rate and demonstrated vulnerability to localized corrosion or cracking in both liquid and vapor phases. Similarly, the L80 grade 13Cr stainless steel is not considered a suitable choice for harsh environments rich in H2S, CO2, and Cl at superheated temperatures. While it was prone to localized corrosion, it exhibited a low uniform corrosion rate ( © 2024 Association for Materials Protection and Performance (AMPP). All rights reserved.

关键词： Localized corrosion

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YOLO-O2E:A Variant YOLO Model for Anomalous Rail Fastening Detection

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computers, Materials & Continua 2024年第7期80卷 1143-1161页

作者： Zhuhong Chu Jianxun Zhang Chengdong Wang Changhui Yang Department of Computer Science and Engineering Chongqing University of TechnologyChongqing400054China Institute of Flexible Electronics(Future Technologies) Xiamen UniversityXiamen361000China College of Mechanical Engineering Chongqing University of TechnologyChongqing400054China

Rail fasteners are a crucial component of the railway transportation safety *** fasteners,distinguished by their high length-to-width ratio,frequently encounter elevated failure rates,necessitating manual inspection and *** inspection not only consumes time but also poses the risk of potential *** the advancement of deep learning technology in rail fasteners,challenges such as the complex background of rail fasteners and the similarity in their states are *** have proposed an efficient and high-precision rail fastener detection algorithm,named YOLO-O2E(you only look once-O2E).Firstly,we propose the EFOV(Enhanced Field of View)structure,aiming to adjust the effective receptive field size of convolutional kernels to enhance insensitivity to small spatial ***,The OD_MP(ODConv and MP_2)and EMA(EfficientMulti-Scale Attention)modules mentioned in the algorithm can acquire a wider spectrum of contextual information,enhancing the model’s ability to recognize and locate ***,we collected and prepared the GKA dataset,sourced from real train *** testing on the GKA dataset and the publicly available NUE-DET dataset,our method outperforms general-purpose object detection *** the GKA dataset,our model achieved a mAP 0.5 value of 97.6%and a mAP 0.5:0.95 value of 83.9%,demonstrating excellent inference ***-O2E is an algorithm for detecting anomalies in railway fasteners that is applicable in practical industrial settings,addressing the industry gap in rail fastener detection.

关键词： Rail fastening detection deep learning anomalous rail fastening variant YOLO feature reinforcement

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MPSleepNet: Matrix Profile-Guided Transformer for Multi-Channel Sleep Classification 24

MPSleepNet: Matrix Profile-Guided Transformer for Multi-Chan...

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7th International Conference on Signal Processing and Machine Learning, SPML 2024

作者： Liu, Huanjing Valderrama, Camilo Zhang, Xingying Liu, Qian The Department of Applied Computer Science The University of Winnipeg Canada The Department of Mechanical Engineering The University of Manitoba Canada

ISBN: (纸本)9798400717192

Polysomnography (PSG)-based sleep staging is vital for assessing sleep quality. As a state-of-the-art deep learning model structure, Transformer has been increasingly utilized to enhance sleep stage classification efficiency. However, the default self-attention mechanism in Transformer encoder often struggles with long-term dependencies in time sequences. To overcome this limitation, we introduce a novel method that integrates the Matrix Profile, a time series data mining technique, with the Transformer's self-attention mechanism to better capture global data abnormalities and temporal dynamics. Our approach preprocesses PSG data from multiple channels using Matrix Profiles to highlight significant patterns. These profiles, combined with time-frequency representations, are fed into a Transformer encoder to fuse multi-channel features, and enhance the understanding of temporal interdependencies. The enhanced features are classified via two fully connected layers, yielding substantial improvements in sleep stage classification accuracy and efficiency on multichannel data as compared to the baseline models. This work not only underscores the efficacy of Matrix Profile in sleep classification but also proposes a new paradigm for processing complex temporal data in deep learning models. The complete code for this model is available at https://***/EliteriaLYU/MPSleepNet. © 2024 ACM.

关键词： Sleep research

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A Framework for Industrial Inspection System using Deep Learning

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Annals of Data science 2024年第2期11卷 445-478页

作者： Hridoy, Monowar Wadud Rahman, Mohammad Mizanur Sakib, Saadman Department of Mechatronics & amp Industrial Engineering Chittagong University of Engineering & ampTechnology Chattogram Bangladesh Department of Mechanical Engineering Chittagong University of Engineering & ampTechnology Chattogram Bangladesh Department of Computer Science & amp Engineering Chittagong University of Engineering & ampTechnology Chattogram Bangladesh

Industrial Inspection systems are an essential part of Industry 4.0. An automated inspection system can significantly improve product quality and reduce human labor while making their life easier. However, a deep learning-based camera inspection system requires a large amount of data to classify the defective products accurately. In this paper, a framework is proposed for an industrial inspection system with the help of deep learning. Additionally, A new dataset of hex-nut products is proposed containing 4000 images, i.e., 2000 defective and 2000 non-defective. Moreover, different CNN architectures, i.e., Custom CNN, Inception ResNet v2, Xception, ResNet 101 v2, ResNet 152 v2, are experimented with the concept of transfer learning on the new hex-nut dataset. Fine-tuning the CNN architectures is performed by freezing the last 14 layers, which provided the optimal architecture, i.e., Xception (last 14 layers trainable, excluding the fully connected layer). The proposed framework can efficiently separate the defective products from the non-defective products with 100% accuracy on the hex nut dataset. Furthermore, the proposed optimal Xception architecture has experimented on a publicly available casting material dataset which produced 99.72% accuracy, outperforming existing methods. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s);author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

关键词： Industry 4.0

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Heat Transfer Area Optimization for Heat Exchanger System

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computer Modeling in engineering & sciences 2025年第4期143卷 335-349页

作者： Yu-Cheng Liao Fu-I Chou Po-Yuan Yang Jyh-Horng Chou Department of Electrical Engineering National Kaohsiung University of Science and TechnologyKaohsiung807Taiwan Department of Intelligent Robotics National Pingtung UniversityPingtung900Taiwan Department of Mechanical and Computer-Aided Engineering Feng Chia UniversityTaichung407Taiwan

This paper presents an allowable-tolerance-based group search optimization(AT-GSO),which combines the robust GSO(R-GSO)and the external quality design planning of the Taguchi ***-GSO algorithm is used to optimize the heat transfer area of the heat exchanger *** R-GSO algorithm integrates the GSO algorithm with the Taguchi method,utilizing the Taguchi method to determine the optimal producer in each iteration of the GSO algorithm to strengthen the robustness of the search process and the ability to find the global *** conventional parameter design optimization,it is typically assumed that the designed parameters can be applied accurately and consistently throughout ***,for systems that are sensitive to changes in design parameters,even minor inaccuracies can substantially reduce overall system ***,the permissible variations of the design parameters are considered in the tolerance-optimized design to ensure the robustness of the *** optimized design of the heat exchanger system assumes that the system’s operating temperature parameters are ***,fixing the systemoperating temperature parameters at a constant value is *** paper assumes that the system operating temperature parameters have an uncertainty error when optimizing the heat transfer area of the heat exchanger *** results show that the AT-GSO algorithm optimizes the heat exchanger system and finds the optimal operating temperature in the absence of tolerance and under three tolerance conditions.

关键词： Heat exchanger system allowable tolerance-based group search optimization Taguchi method tolerance design

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