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A Data-driven Pattern Design Method for Watertight Plush Toy Models

computer-Aided Design and Applications 2023年第1期20卷 28-43页

作者： Jin, Yinghan Wang, Jin Li, Jituo Zhang, Dongliang College of Computer Science Zhejiang University China School of Mechanical Engineering Zhejiang University China

This paper presents an automatic pattern design method for plush toys using a data-driven approach. For a watertight toy model, we use a divide-andconquer strategy to convert it into a component-based model, then automatically design patterns of each component. Firstly, a segmentation and componentization method based on deep learning is proposed to decompose a 3D watertight model into several meaningful components. Then, the most similar component template is retrieved and used to generate seam lines of the model. Finally, 2D patterns of the toy model are obtained by flattening 3D surface patches. The segmentation and componentization method can also be used to easily edit the shape and structure of a watertight model. Experimental results show that reasonable patterns can be designed automatically and efficiently using the proposed method. © 2023 CAD Solutions, LLC.

关键词： Toys

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An efficient integrity based multi-user blockchain framework for heterogeneous supply chain management applications

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International Journal of computers and Applications 2023年第4期45卷 337-351页

作者： Karumanchi, Mani Deep Sheeba, J.I. Devaneyan, S. Pradeep Department of Computer Science and Engineering Bapatla Engineering College Bapatla India Department of Computer Science and Engineering Puducherry Technological University Puducherry India Department of Mechanical Engineering Sri Venkateshwaraa College of Engineering and Technology Puducherry India

Most of the traditional cloud-based applications are insecure and difficult to compute the data integrity with variable hash size on heterogeneous supply chain datasets. Also, cloud storage systems are independent of integrity computational and data security due to structured data and computational memory. As the size of the cloud data files is increasing in the public and private cloud servers, it is difficult to provide strong data security due to file format and high dimensionality. The computational time and storage space of the conventional attribute-based encryption and decryption models are high during the data integrity verification in the traditional blockchain frameworks. This paper implements a hybrid variable size data integrity algorithm on the heterogeneous cloud supply chain data files for the strong data encryption and decryption process. This work implements an optimized blockchain framework using the advanced heterogeneous integrity computation approach and integrity policy-based attribute encryption and decryption approach for better cloud data security. Experimental results proved that the proposed integrity-based encryption model has better efficiency than the traditional integrity-based encryption frameworks on cloud heterogeneous data types. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Blockchain

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Experimental investigation on machining of titanium composite using artificial neural network

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Interactions 2025年第1期246卷 1-10页

作者： Perumal, B. Kannan, R. Arunkumar, R. Kumaresan, T. Subbiah, Ram Department of Mechanical Engineering Sri Venkateshwara College of Engineering Andhra Pradesh Tirupati India Department of Mechanical Engineering PSNA College of Engineering and Technology Dindigul India Department of Mechanical Engineering MRK Institute of Technology Tamilnadu Kattumannarkoil India Department of Computer Science and Engineering Bannari Amman Institute of Technology Sathyamangalam Erode India Department of Mechanical Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad India

Manufacturers must be able to figure out the most suitable technique capable of generating rapid and accurate performance when developing a precise modelling approach for the development of an efficient machining process. This paper assesses the predictive capabilities of the Artificial Neural Network (ANN) and the response surface methodology in the titanium machining process with respect to tool tip temperature and tool wear. The adequacy of the ANN in modeling and forecasting reactions were rigorously examined and contrasted using data collected from properly prepared machining experiments. Both approaches performed admirably in terms of forecasting machining process responses. The coefficient of correlation (R2) obtained from the analysis verifies the ANN’s choice, with a maximum value of 99.9% and with the response surface methodology with a maximum value of 99.8% was found. The experiment also demonstrates that when the proper parameters are used, the ANN approach can produce the best results. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Machining centers

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Exploring Deep Learning Methods for computer Vision Applications across Multiple Sectors:Challenges and Future Trends

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computer Modeling in engineering & sciences 2024年第4期139卷 103-141页

作者： Narayanan Ganesh Rajendran Shankar Miroslav Mahdal Janakiraman SenthilMurugan Jasgurpreet Singh Chohan Kanak Kalita School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaram522502India Department of Control Systems and Instrumentation Faculty of Mechanical EngineeringVSB-Technical University of OstravaOstrava70800Czech Republic Department of Computer Science and Engineering Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India Department of Mechanical Engineering and University Centre for Research&Development Chandigarh UniversityMohali140413India Department of Mechanical Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyAvadi600062India

computer vision(CV)was developed for computers and other systems to act or make recommendations based on visual inputs,such as digital photos,movies,and other *** learning(DL)methods are more successful than other traditional machine learning(ML)methods *** techniques can produce state-of-the-art results for difficult CV problems like picture categorization,object detection,and face *** this review,a structured discussion on the history,methods,and applications of DL methods to CV problems is *** sector-wise presentation of applications in this papermay be particularly useful for researchers in niche fields who have limited or introductory knowledge of DL methods and *** review will provide readers with context and examples of how these techniques can be applied to specific areas.A curated list of popular datasets and a brief description of them are also included for the benefit of readers.

关键词： Neural network machine vision classification object detection deep learning

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Optimization of process parameters in 3D printing of polycarbonate for high heat applications

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Interactions 2024年第1期245卷 1-21页

作者： Srinivas, Bathula Satishkumar, P. Saminathan, Rajasekaran Srikanth, Barre Andhra Pradesh Odalarevu533210 India Department of Mechanical Engineering Rathinam Technical Campus Coimbatore Tamil Nadu Coimbatore India Department of Mechanical Engineering College of Engineering and computer science Jazan University Jizan Saudi Arabia

This experimentation conducts for the optimization of Polycarbonate(PC) material 3D printing factors. The printing is done on the Flash Forge Guider 2 FDM equipment, employing the Taguchi methodology. The factors considered for optimization include infill rate (60%, 80%, 100%), film height (0.18 mm, 0.24 mm, 0.30 mm), and printing speed (40 mm/s, 60 mm/s, 80 mm/s). Tensile, compressive, and flexural experiments were performed to examine the mechanical properties of the printed objects. The experimental results revealed the highest tensile strength (39.106 MPa) at an infill rate of 100%, printing speed of 40 mm/s, and film thickness of 0.30 mm. As well as, the greatest compressive toughness (76.421 MPa) was produced at a fill density of 100%, printing rate of 60 mm/s, and layer thickness of 0.18 mm. The flexural toughness carried its peak (253.1 MPa) at an infill rate of 100%, printing rate of 40 mm/s, and film thickness of 0.30 mm. Using Signal-Noise (S/N) ratio charts, the maximum factors for improving tensile toughness were resolved as infill rate 100%, printing speed 40 mm/s, and film height 0.24 mm. For compressive toughness development, the maximum factors were detected as infill rate 100%, printing speed 60 mm/s, along with film height 0.18 mm. Flexural toughness optimization showed the infill rate 100%, printing speed 80 mm/s, along with film height 0.30 mm. Analysis of Variance (ANOVA) recommended the important contributions of every factor to the mechanical props. For tensile toughness, infill rate provides 93.37%, printing speed 0.121%, along with film height 4.17%. Compressive toughness development was provided to infill rate (87.48%), printing speed (3.81%), along with film height (2.38%). In the case of flexural toughness, infill rate provides 47.36%, printing speed 0.96%, along with film height 50%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Tensile strength

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Enhancing mechanical durability and flame retardancy in Bamboo-Polypropylene composites with nAl2O3 fillers

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Interactions 2024年第1期245卷 1-17页

作者： Sahare, Shilpa B. Seenivasan, S. Satishkumar, P. Lajurkar, Sangita Pravin Saminathan, Rajasekaran Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Maharashtra Nagpur India Department of Mechanical Engineering Rathinam Technical Campus Tamilnadu Coimbatore India Department of Civil Engineering Acharya Shrimannarayan Polytechnic Maharashtra Pipri Wardha India Department of Mechanical Engineering College of Engineering and Computer Science Jazan University Jazan Saudi Arabia

Natural fiber-based nanocomposite is an innovative material created recently, widely used in various industries for its exceptional strength-to-weight ratio and lightweight properties. The study examined the impact of titanium nanoparticles on the mechanical properties, moisture absorption, flammability, and dynamic mechanical characteristics of polypropylene (PP)/Bamboo fiber. Composite materials consisting of PP, Bamboo fiber, and alumina were manufactured using injection molding. The hybrids’ elongation at break (1.70%), tensile strength (TS), and modulus of elasticity (2124 MPa, 43.1 MPa, and 9%, respectively), were enhanced by adding 9% nano aluminum oxide (nAl2O3) nanoparticles to the mix. The clean PP/Bamboo had a modulus of 2189 MPa and bending strength of 39.6 MPa. The PP/Bamboo/Al2O3 composite material showed a modulus of 2805 MPa and a bending strength of 56.7 MPa, an increase of 28.46%. Raised nanoparticle concentration resulted in a significant reduction in water absorption (9.1%) and swelling thickness (2.03%). The n-Al2O3 was incorporated into composites to improve their dynamic mechanical properties, resulting in a loss modulus of 5.02 MPa and a storage modulus of 12.92 MPa. Additionally, it enhanced fire resistance, leading to a combustion rate of 18 mm min-1 and a char residue of 30%. The endurance of the char barrier is greatly affected by the chemical composition and distribution pattern of the mixture. Char shields with increased nAl2O3 content are designed to resist burning and require greater temperatures to break down. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Tensile strength

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Optimized and reliable nose cone layout for a non-control hypersonic flying vehicle

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Aerospace Systems 2025年 1-18页

作者： Nadjafi, Mohammad Malekian, Mohammad Amin Kia, Mostafa Abbasi Tehran Iran Mechanical Engineering Department Tarbiat Modares University Tehran Iran Department of Computer Science Lorestan University Lorestan Khorramabad Iran

Ballistic missiles are perhaps the most critical and common flying devices today, flying at very high altitudes compared to aeroplanes. Among the important points about these flying devices is their very high speed in the final phase, usually several times the speed of sound. Choosing essential design parameters for making these devices has always been a significant challenge for designers. Structural, propulsion, aerodynamic, and control parameters are the most influential. The topic of nose cone aerodynamics is one of the essential design components to achieve the most reliable and optimal designs. Deciding the right nose cone has been one of the main challenges in recent years in this field. This article aims to review and analyse some examples of standard nose cones with this structure. For this purpose, first, the arrangement and layout of various designs and their specifications have been presented. The nose cone modelling has been performed for all modes, and each layout's results have been introduced. Finally, a model based on the results is proposed, the most optimal and reliable arrangement based on aerodynamic parameters. © Shanghai Jiao Tong University 2025.

关键词： Ballistic missiles

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ASL-OOD:Hierarchical Contextual Feature Fusion with Angle-Sensitive Loss for Oriented Object Detection

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computers, Materials & Continua 2025年第2期82卷 1879-1899页

作者： Kexin Wang Jiancheng Liu Yuqing Lin Tuo Wang Zhipeng Zhang Wanlong Qi Xingye Han Runyuan Wen Northwest Institute of Mechanical and Electrical Engineering Xianyang712099China School of Information Engineering Chang’an UniversityXi’an710064China School of Computer Science and Technology Xidian UniversityXi’an710071China

Detecting oriented targets in remote sensing images amidst complex and heterogeneous backgrounds remains a formidable challenge in the field of object *** frameworks for oriented detection modules are constrained by intrinsic limitations,including excessive computational and memory overheads,discrepancies between predefined anchors and ground truth bounding boxes,intricate training processes,and feature alignment *** overcome these challenges,we present ASL-OOD(Angle-based SIOU Loss for Oriented Object Detection),a novel,efficient,and robust one-stage framework tailored for oriented object *** ASL-OOD framework comprises three core components:the Transformer-based Backbone(TB),the Transformer-based Neck(TN),and the Angle-SIOU(Scylla Intersection over Union)based Decoupled Head(ASDH).By leveraging the Swin Transformer,the TB and TN modules offer several key advantages,such as the capacity to model long-range dependencies,preserve high-resolution feature representations,seamlessly integrate multi-scale features,and enhance parameter *** improvements empower the model to accurately detect objects across varying *** ASDH module further enhances detection performance by incorporating angle-aware optimization based on SIOU,ensuring precise angular consistency and bounding box *** approach effectively harmonizes shape loss and distance loss during the optimization process,thereby significantly boosting detection *** evaluations and ablation studies on standard benchmark datasets such as DOTA with an mAP(mean Average Precision)of 80.16 percent,HRSC2016 with an mAP of 91.07 percent,MAR20 with an mAP of 85.45 percent,and UAVDT with an mAP of 39.7 percent demonstrate the clear superiority of ASL-OOD over state-of-the-art oriented object detection *** findings underscore the model’s efficacy as an advanced solution for challenging remote sensing object detection tasks.

关键词： Oriented object detection transformer deep learning

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A Terramechanics-based Dynamic Model for Motion Control of Unmanned Tracked Vehicles

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-14页

作者： Zhang, Ruizeng Zhou, Wei Liu, Haiou Gong, Jianwei Chen, Huiyan Khajepour, Amir School of Mechanical Engineering Beijing Institute of Technology Beijing China School of Computer Science and Informatics Cardiff University Cardiff U.K Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo Canada

Existing terramechanics-based dynamic models for tracked vehicles (TRVs) are widely used in dynamics analysis. However, these models are incompatible with model-based controller design due to their high complexity and computational costs. This study presents a novel and simplified terramechanics-based dynamic model for TRVs that can be used in optimization-based real-time motion controller design. To this end, we approximated the track-ground interactions with an averaged term of the track-ground shear stresses to make the model computationally efficient and linearizable. By introducing the concepts of slip ratio and slip angle in the field of wheeled vehicles, the terramechanics-based dynamic model was finally simplified into a compact and practical single-track dynamic model reducing the demand for precise slip ratio measurements. The single-track model enables us to design an efficient motion control scheme by considering lateral and longitudinal dynamics separately. Finally, the proposed dynamic model was verified and validated under various road conditions using a real TRV. Additionally, the performance of different models was compared in simulation as an example to demonstrate that the proposed model outperforms the existing ones in TRV path-following tasks. IEEE

关键词： Model predictive control

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A two-dimensional MoS_(2) array based on artificial neural network learning for high-quality imaging

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Nano Research 2023年第7期16卷 10139-10147页

作者： Long Chen Siyuan Chen Jinchao Wu Luhua Chen Shuai Yang Jian Chu Chengming Jiang Sheng Bi Jinhui Song School of Mechanical Engineering Dalian University of TechnologyDalian 116024China School of Computer Science Southwest Petroleum UniversityChengdu 610500China

As the basis of machine vision,the biomimetic image sensing devices are the eyes of artificial *** recent years,with the development of two-dimensional(2D)materials,many new optoelectronic devices are developed for their outstanding ***,there are still little sensing arrays based on 2D materials with high imaging quality,due to the poor uniformity of pixels caused by material defects and fabrication ***,we propose a 2D MoS_(2)sensing array based on artificial neural network(ANN)*** equipping the MoS_(2)sensing array with a“brain”(ANN),the imaging quality can be effectively *** the test,the relative standard deviation(RSD)between pixels decreased from about 34.3%to 6.2%and 5.49%after adjustment by the back propagation(BP)and Elman neural networks,*** peak signal to noise ratio(PSNR)and structural similarity(SSIM)of the image are improved by about 2.5 times,which realizes the re-recognition of the distorted *** provides a feasible approach for the application of 2D sensing array by integrating ANN to achieve high quality imaging.

关键词： two-dimensional MoS_(2) sensing array artificial neural network individual difference imaging quality

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