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PATH GENERATIVE MODEL BASED ON CONDITIONAL β- VARIATIONAL AUTO ENCODER FOR MECHANISM design

PATH GENERATIVE MODEL BASED ON CONDITIONAL β- VARIATIONAL A...

ASME 2024 International design engineering Technical Conferences and computers and Information in engineering Conference, IDETC-CIE 2024

作者： Nurizada, Anar Lyu, Zhijie Purwar, Anurag Computer-Aided Design and Innovation Lab Department of Mechanical Engineering Stony Brook University Stony BrookNY11794-2300 United States

ISBN: (纸本)9780791888414

This paper introduces a novel methodology based on Conditional β-Variational Autoencoder (cβ-VAE) architecture to generate diverse types of planar four-bar mechanisms for a given coupler curve. This approach allows for the synthesis of linkages capable of tracing continuous paths, overcoming the overdetermined problem often encountered in linkage coupler-curve synthesis. The proposed deep generative model processes mechanisms alongside their coupler curves and types, generating a latent vector that enables the decoder to produce a variety of mechanisms tailored to specific conditions. The paper also introduces a comprehensive methodology for assessing the efficacy of the model, proposing three hierarchical metrics focused on reconstruction quality, novelty, and diversity of the predicted mechanisms. The methodology is scalable and applicable to various types of four-bar and higher-order mechanisms, enhancing the model's utility by including an additional step for computing cognates of predicted mechanisms, thereby generating more efficient solutions. The key contributions of this work lie in the development of a Conditional β-VAE model with attention layers for synthesizing multiple mechanisms, the creation of a unified representation for different types of four-bar mechanisms, the generation of an extensive dataset, the development of a unified algorithm for computing cognates, and the introduction of quantitative assessment metrics. This approach not only surmounts the limitations of traditional methods but also opens new avenues for mechanism design, providing a data-driven tool for exploring alternative designs and evaluating their performance in real-time. Copyright © 2024 by ASME.

关键词： Machine design

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Computational Model of Swarm Algorithm for Optimizing Process of Keywords Extraction from Text Information Presented as Graph 7

Computational Model of Swarm Algorithm for Optimizing Proces...

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7th International Conference on Information Technologies in engineering Education, Inforino 2024

作者： Kravchenko, Yury Kuliev, Elmar Kravchenko, Daniil Rodzin, Sergey Pavlov, Nikolay Rodzina, Lada Southern Federal University Dept. of Computer Aided Design Taganrog Russia Southern Federal University Department of Software Engineering Taganrog Russia

ISBN: (纸本)9798350371369

The article describes the scientific problem of optimizing the processes of acquiring knowledge when processing textual information presented in the form of a graph, based on the development of a modified bioinspired algorithm for extracting keywords. The solution proposed by the authors differs from the known ones by introducing new attractive operators and behavioral patterns of bacterial agents into the computational model of the bacterial swarm algorithm. This approach allows you to balance the ratio of the speed of convergence of the algorithm with the diversification of the search space for solutions. The article also presents an analytical study of the features of two types of parsing: constituency parsing and dependency parsing. As part of the study, algorithms for syntactic parsing of dependencies between elements of text information and a graph-based dependency parsing algorithm are described. The formulation of the problem of keyword extraction is given. The task of achieving a balance between accuracy and speed of a linguistic parser is an open topic that requires further research due to the importance of this problem for improving the efficiency of text analysis, especially in applications that require real-time accuracy. To increase the efficiency of solving the problem, the authors propose a modified bioinspired algorithm for extracting keywords. The computational experiment carried out allows us to conclude that the modified bacterial optimization method proposed by the authors is in a leading position, which confirms the need to continue research into the applicability of bioinspired methods for solving problems of acquiring knowledge when processing text information presented in the form of a graph. This article is focused on the direction of study in the master's program "Informatics and computer Science", as well as the scientific specialty of postgraduate training "Artificial Intelligence and Machine Learning". © 2024 IEEE.

关键词： Text processing

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SYNTHESIZING SPATIAL RSCR MECHANISMS FOR PATH GENERATION USING A DEEP NEURAL NETWORK

SYNTHESIZING SPATIAL RSCR MECHANISMS FOR PATH GENERATION USI...

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ASME 2024 International design engineering Technical Conferences and computers and Information in engineering Conference, IDETC-CIE 2024

作者： Deng, Xueting Nurizada, Anar Purwar, Anurag Computer-Aided Design and Innovation Lab Department of Mechanical Engineering Stony Brook University Stony BrookNY11794-2300 United States

ISBN: (纸本)9780791888414

In the recent past, various machine learning approaches have been broadly studied and successfully applied in the planar mechanism synthesis problem. This paves the way for its adoption in the spatial mechanism synthesis that is typically more complex to solve due to dimensionality of the input, large number of mechanism parameters, and highly non-linear relationship between the input and output. This paper introduces a neural network approach for the path synthesis of spatial RSCR mechanisms. We detail the method of database generation with the development of a simulator, data space selection strategies, and a complete data normalization method. A novel way of calculating the coupler curve is utilized, addressing the challenge of describing the absolute position of a point on the rigid body in R3. The database generation uses a spatial mesh grid-base method with specific criteria for preventing circuit defects and duplicate mechanisms. All data in the database is translated, rotated, and reflected to a normalized position. In the end, the classical neural network structure, multi-layer perceptron (MLP), is applied for finding the mapping from the spatial path to mechanism parameters. The MLP with different parameters and techniques, such as batch normalization and dropout, are implemented for finding the best model. The result shows the capability of MLP for complex spatial path synthesis. Moreover, despite the limitation of a single MLP's structure, this study demonstrates the potential of improvement with more advanced neural networks. Copyright © 2024 by ASME.

关键词： Deep neural networks

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GENERATIVE design OF PLANAR FOUR-BAR MOTIONS USING CONDITIONAL VARIATIONAL AUTOENCODER

GENERATIVE DESIGN OF PLANAR FOUR-BAR MOTIONS USING CONDITION...

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ASME 2024 International design engineering Technical Conferences and computers and Information in engineering Conference, IDETC-CIE 2024

作者： Halwah, Amro Nurizada, Anar Purwar, Anurag Computer-Aided Design and Innovation Lab Department of Mechanical Engineering Stony Brook University Stony BrookNY11794-2300 United States

ISBN: (纸本)9780791888360

This paper introduces a novel deep generative approach to the approximate motion synthesis of planar four-bar mechanisms. Existing motion synthesis approaches for synthesizing four-bar mechanisms have generally focused on representing the motion as five or less discrete poses while not providing any guarantees on the practicality of the solutions, such as ones without circuit-, branch-, and order-defects. This paper presents a Conditional Variational Autoencoder (C-VAE) based approach for synthesizing practical mechanisms that can capture the overall motion requirement while generating a continuous motion approximately. The mathematical machinery in our work uses quaternion and kinematic mapping to represent the geometric constraints of dyads of four-bar mechanism as algebraic constraint manifolds in a three-dimensional projective space. The parameters describing the manifolds encode information about the type and dimensions. These parameters are used as input to a C-VAE that uses an arbitrarily large number of input poses approximating a motion as the condition. A procedure is presented for normalizing input motions such that they are invariant with respect to rotation, scaling, translation and reflection. The trained model can generate several pairs of constraint manifolds from which four-bar mechanisms with different parameters can be retrieved. These mechanisms’ coupler poses approximate the input’s coupler poses to varying degrees of error. A method for filtering mechanisms by the quality of match of their output motion to the input motion is also proposed. Different metrics for quantifying the similarity of an output mechanism’s motion with the input motion are presented for path and orientation separately. Copyright © 2024 by ASME.

关键词： Variational techniques

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Robust CNN for facial emotion recognition and real-time GUI

AIMS Electronics and Electrical Engineering

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AIMS Electronics and Electrical engineering 2024年第2期8卷 217-236页

作者： Ali, Imad Ghaffar, Faisal Department of Computer Science University of Swat KP Swat Pakistan System Design Engineering Department University of Waterloo Waterloo Canada

computer vision is witnessing a surge of interest in machines accurately recognizing and interpreting human emotions through facial expression analysis. However, variations in image properties such as brightness, contrast, and resolution make it harder for models to predict the underlying emotion accurately. Utilizing a robust architecture of a convolutional neural network (CNN), we designed an efficacious framework for facial emotion recognition that predicts emotions and assigns corresponding probabilities to each fundamental human emotion. Each image is processed with various pre-processing steps before inputting it to the CNN to enhance the visibility and clarity of facial features, enabling the CNN to learn more effectively from the data. As CNNs entail a large amount of data for training, we used a data augmentation technique that helps to enhance the model's generalization capabilities, enabling it to effectively handle previously unseen data. To train the model, we joined the datasets, namely JAFFE and KDEF. We allocated 90% of the data for training, reserving the remaining 10% for testing purposes. The results of the CCN framework demonstrated a peak accuracy of 78.1%, which was achieved with the joint dataset. This accuracy indicated the model's capability to recognize facial emotions with a promising level of performance. Additionally, we developed an application with a graphical user interface for real-time facial emotion classification. This application allows users to classify emotions from still images and live video feeds, making it practical and user-friendly. The real-time application further demonstrates the system's practicality and potential for various real-world applications involving facial emotion analysis. © 2024 the Author(s).

关键词： Graphical user interfaces

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Mathematical Model for Plate Elastic Properties Studying Based on Its Amplitude-Frequency Characteristics 28

Mathematical Model for Plate Elastic Properties Studying Bas...

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28th IEEE International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory, DIPED 2023

作者： Rebot, Dariia Stefanovych, Tetyana Shcherbovskykh, Serhiy Computer-Aided Design System Department Lviv Polytechnic National University Lviv Ukraine

ISBN: (纸本)9798350315332

the article describes a mathematical model for studying the elastic properties of a plate on its amplitude-frequency characteristics under the influence of an external disturbance. The methods of nonlinear mechanics were used to build the mathematical model. Based on the obtained equations, graphical dependences of amplitude-frequency characteristics for soft, linear, and rigid systems are constructed. The obtained results can be used in future studies of oscillatory processes in resonators. © 2023 IEEE.

关键词： Elasticity

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Survey on Recommendation System Combining Hybrid and Popularity Based Approach 2

Survey on Recommendation System Combining Hybrid and Popular...

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2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Bhogan, Snehal Naik, Sagar Gaonkar, Suhesha Prabhudesai, Sharvil Dhond, Gaurish Fernandes, Kevin Agnel Institute of Technology and Design Department of Computer Engineering India

ISBN: (纸本)9798350327533

The rapidly developing e-commerce environment offers consumers a multitude of products and services, making it difficult to find products that suit their interests and budgets. This research work presents a solution consisting of individualized based recommendations on user's behavior and preferences, and base them on the user's shared *** order to enhance user experience,it shows the use of a recommendation model that estimates specific product that a user may wish to buy using a hybrid system and a popularity-based system. This research work places a strong emphasis on data veracity, quality modeling, and user privacy protection. The system is designed to make purchasing decisions easier for e-commerce customers by providing them with information about competitive pricing and product recommendations. It provides e-commerce and research data to create effective solutions to improve online business, creating a win-win situation for the consumer and e-commerce. © 2024 IEEE.

关键词： Hybrid Popularity Recommendation Model

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Performance Evaluation of YOLO variants on Marine Trash Images: A Comparative Study of YOLOv5, YOLOv7, YOLOv8, and TinyYOLO

Performance Evaluation of YOLO variants on Marine Trash Imag...

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2024 IEEE Bangalore Humanitarian Technology Conference, B-HTC 2024

作者： Sawant, Shreedatta D'Souza, Lyzandra Kulkarni, Aditi Uchil, Devika Nagvenkar, Krisha Agnel Institute of Technology and Design Department of Computer Engineering India

ISBN: (纸本)9798350344509

Despite the growing efforts to tackle the issue of marine pollution, the accurate and effective detection of oceanic litter remains a chronic difficulty. The development of a reliable deep learning-based system is vital for accurate and rapid marine trash detection in order to address these issues. This study delves into the comparison of the YOLO (You Only Look Once) variants, YOLOv4 tiny, YOLOv5, YOLOv7, and YOLOv8 so as to identify the best model for underwater plastic waste detection. The results of the experiment show that YOLOv5 has the highest mAP@50 at 0.92 and YOLOv5 also has a higher recall and F1-score compared to the other three models. Our findings also revealed that YOLOv7 had the smallest mAP@50, measuring at 0.847. © 2024 IEEE.

关键词： Marine pollution

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Enhancing coordinated target tracking: innovative particle filters with meta-heuristic integration and advanced model validation

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Soft Computing 2025年第7期29卷 1-32页

作者： Das, Nitish Kulkarni, Nilima Department of Computer Science and Engineering MIT Art Design and Technology University Loni Kalbhor Pune412201 India

Coordinated target tracking and its augmented variant represent significant challenges in modern surveillance. These tasks are essential for accurately localizing and predicting the movement of dynamic targets. This article introduces an advanced particle filter algorithm with a packet dropout mechanism to enhance tracking accuracy. Additionally, it proposes three meta-heuristic-driven particle filters: the Particle Filter integrated with the Chaotic Gravitational Search Algorithm (PF-CGSA), the Particle Filter integrated with the Improved Grey Wolf Optimizer (PF-IGWO), and the Particle Filter integrated with the Imperialist Competitive Algorithm with Regional Domination Policy (PF-ICARD). These methods are tested using three sophisticated models: the Coordinated Turn Target Tracking Model (CT model), the Augmented Coordinated Turn Target Tracking Model with Cartesian Velocity (ACT1 model), and the Augmented Coordinated Turn Target Tracking Model with Polar Velocity (ACT2 model). Experimental results demonstrate that PF-CGSA, PF-IGWO, and PF-ICARD achieve higher convergence speeds and accuracy. They also effectively mitigate premature convergence phenomena. Comparative analysis based on Root Mean Squared Error (RMSE) metrics underscores their superiority in real-world target tracking challenges, highlighting the potential of these advanced particle filtering techniques in enhancing precision and efficiency in target tracking. Particularly, PF-ICARD achieves the highest accuracy, reducing RMSE by up to 18.64% compared to PF-CGSA and PF-IGWO, making it ideal for high-precision applications. PF-CGSA excels in specific scenarios, notably improving X-coordinate tracking in the ACT2 model by up to 11.39%. Meanwhile, PF-IGWO offers a balanced solution with moderate accuracy and enhanced computational efficiency, suitable for real-time applications. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Aircraft detection

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Development of Microcontroller-Based Pure Sine Wave Inverter with Overload and Overheating Protection 17

Development of Microcontroller-Based Pure Sine Wave Inverter...

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Holovatyy, Andriy Lobur, Mykhaylo Holovata, Sofia Lukaszewicz, Andrzej Nowakowski, Marek Kolesnyk, Kostyantyn Lviv Polytechnic National University Department of Computer-Aided Design Systems Lviv Ukraine Ukrainian National Forestry University Department of Software Engineering Lviv Ukraine Bialystok University of Technology Department of Machinery Design and Operation Bialystok Poland Military Institute of Armoured and Automotive Technology Development Department Sulejowek Poland Lviv Polytechnic National University Department of Computera-Aided Design Systems Lviv Ukraine

ISBN: (纸本)9798331520564

In the paper, hardware and software of the Arduino based pure sine wave inverter with overload and overheating protection have been developed. The inverter constantly monitors the consumption current, the battery voltage, the temperature of the power switches (radiator) and, if their parameters are normal, forms a sinusoidal voltage of 230 V, 50 Hz at the output of the inverter, similar to the network voltage. The inverter provides the display of information on the LCD screen about current and power consumption, battery voltage, temperature of the inverter power switches, as well as display of emergency icons when the permissible operating parameters are exceeded. The inverter generates sound and visual warning messages with LED indicators and buzzer. The inverter can be used as a lightweight low-power 100 W network inverter with sine-wave voltage for autonomous power supply of low-power electronics. © 2024 IEEE.

关键词： Microcontrollers

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