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Medicine Powder Inspection by Image processing Technique 8

Medicine Powder Inspection by Image Processing Technique

引用

8th IEEE/ACIS international conference on Big Data, Cloud Computing, and Data Science, BCD 2023

作者： Moses, Reynard Peng, Cheng-Yu Hsieh, Cho-Fan Lin, Kao-Chi National Chin-Yi University of Technology Department of Electronic Engineering Taiwan Industrial Technology Research Institute Center for Measurement Standards Taiwan

ISBN: (纸本)9798350373615

this work presents medicine powder inspection by image processing techniques using RGB camera acquisition. the light intensity in the environment and the angle of incident light make judgment difficult. the defect particles are buried in the medicine powder making detection impossible to clearly distinguish. Several images are applied to obtain the size and location of foreign matter inside the medicine bottle by the image operators of machine vision and from the equipment design to image acquisition. © 2023 IEEE.

关键词： Defects

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ICMAI 2023 - 2023 8th international conference on mathematics and Artificial Intelligence

ICMAI 2023 - 2023 8th International Conference on Mathematic...

引用

8th international conference on mathematics and Artificial Intelligence, ICMAI 2023

ISBN: (纸本)9781450399982

the proceedings contain 14 papers. the topics discussed include: GBCloud: a robust cloud model for processing multi-dimensional data using granular-ball computing;forecasting dining times in a full-service thai hotpot restaurant using random forest classifier;GBSMOTE: a robust sampling method based on granular-ball computing and SMOTE for class imbalance;fuzzy Fourier transform under nonabsolute fuzzy integrals;majority colorings of some special digraphs;FWNRS: a fast attribute reduction algorithm based on weighted neighborhood rough set;an adaptive granular ball classifier based on natural neighbor;SuperGlue-based deep learning method for image matching from multiple viewpoints;building interpretable deep CNN based on binary tree structure convolution layers;and research on embedded deployment optimization method of neural network.

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Towards parallel Algorithms for Gromov-Witten Invariants of Elliptic Curves 8th

Towards Parallel Algorithms for Gromov-Witten Invariants of ...

引用

8th international conference on Mathematical Software (ICMS)

作者： Traore, Ali RPTU Fachbereich Math D-67653 Kaiserslautern Germany

ISBN: (纸本)9783031645280;9783031645297

We present a parallel enhanced algorithm for exploring mirror symmetry for elliptic curves through the correspondence of algebraic and tropical geometry, focusing on Gromov-Witten invariants of elliptic curves and, in particular, Hurwitz numbers. We present a new highly efficient algorithm for computing generating series for these numbers. A sequential version of the algorithm has been implemented using Singular and OSCAR. the implementations in [1] outperform by far the previous methods [3] provided in Singular. In this note, we describe work towards the natural next step, which is parallelization. We have integrated our algorithm with GPI-Space, a workflow management system for high-performance computing developed at Fraunhofer ITWM. this allows us to run our algorithm simultaneously on a large number of cores. this facilitates computation of quasi-modular representations of the respective generating series.

关键词： Mirror symmetry Gromov-Witten invariants Feynman integrals massively parallel computations parallel algorithms for combinatorics GPI-Space

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Using parallel Performance Data to Classify parallel Algorithms 15th

Using Parallel Performance Data to Classify Parallel Algorit...

引用

15th international conference on parallel processing and applied mathematics, PPAM 2024

作者： McKinsey, Michael Brink, Stephanie Pearce, Olga Texas A&M University College StationTX United States Lawrence Livermore National Laboratory LivermoreCA United States

ISBN: (纸本)9783031856969

Can we tell which parallel algorithm is executing by looking at the performance of the algorithm? In this work, we design and demonstrate a study for parallel algorithm classification of parallel sorting algorithms. We leverage Caliper to collect the performance data, and thicket for our exploratory data analysis (EDA). For classification, we develop a workflow with PyTorch and Scikit-learn to evaluate the effectiveness of support vector machines (SVMs), neural networks, and decision trees on parallel performance data. We demonstrate classification accuracy for these three different models of 95.3%, 94.0%, and 90.1% across five different parallel algorithm classes. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Data accuracy

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A Robot Gripper with Differential and Hoeckens Linkages for Straight parallel Pinch and Self-Adaptive Grasp 8

A Robot Gripper with Differential and Hoeckens Linkages for ...

引用

8th IEEE international conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Liu, Yankai Zhang, Wenzeng School of Mechanical Engineering and Automation Beihang University Beijing100191 China X-Institute Shenzhen518122 China

ISBN: (纸本)9798350300178

For grasp modes, parallel pinch is one of the significant way of them. the traditional parallel pinching and self-adaption device moves with arc-shaped motion at phalanx terminal, requiring the assistance of an industrial robotic arm for lifting motion, making using it with inconvenience. So as to settle the issue, Hoeckens finger - a kind of novel robot finger is modeled and produced. the Hoeckens linkage mechanism is adopted for achieving the linear motion of the terminal joint in this finger. the mechanism of differential on phalanx surface is set for achieving shape self-adaptation of two phalanxes. And the parallel four-bar has the ability to keep attitude. Above designs achieve the underactuated gripper. After grasping force and motion analysis of Hoeckens fingers, the optimized parameters can be attained. then the Hoeckens gripper is produced. With results of experiments, the Hoeckens gripper achieves the straight parallel pinching and self-adaption grasping function, with large grasp range, stable grasp effect. the Hoeckens gripper can be used to capture objects in more conditions. © 2023 IEEE.

关键词： Grippers

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Deep reinforcement learning for solving hybrid flow shop scheduling problem with unrelated parallel machines 8

Deep reinforcement learning for solving hybrid flow shop sch...

引用

8th international conference on Intelligent Computing and Signal processing, ICSP 2023

作者： Luo, Jing Wang, Bailin Yuan, Shuaipeng Zhang, Wenxin Li, Tieke University of Science and Technology Beijing School of Economics and Management China Ministry of Education Engineering Research Center of Mes Technology for Iron & Steel Production Beijing China

ISBN: (纸本)9798350302455

For the hybrid flow shop scheduling problem with unrelated parallel machines with dynamically arrived jobs, an online scheduling method is proposed based on Deep-Q-Network (DQN) and scheduling rules to minimize total tardiness. In order to optimize production scheduling and minimize tardiness, we combine classic scheduling rules with the proposed DQN algorithm. the algorithm selects jobs and assigns them to feasible machines based on their completion or arrival time, while seven state features represent the production status at each scheduling point. We validate our approach through numerical experiments on various production configurations, showing significant advantages over traditional scheduling rules. © 2023 IEEE.

关键词： Reinforcement learning

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Platform Independent Satellite Image processing Using GPGPU 1

引用

8th international conference on Data Management, Analytics and Innovation, ICDMAI 2024

作者： Kanjalkar, Jyoti Natu, Atharv Patel, Uttkarsh Sonawane, Harshal Patil, Manasi Kanjalkar, Pramod Vishwakarma Institute of Technology Pune India

ISBN: (数字)9789819732456

ISBN: (纸本)9789819732449

the volume of multimedia data is increasing in areas such as big data analytics, image processing, and computer vision, making it challenging to interpret and use information efficiently. Traditional methods for processing such data need a lot of time and resources. the proposed system seeks to identify significant changes in environmental parameters using various image processing techniques while allowing hardware and operating system independence. this study suggests the use of parallel programming frameworks like CUDA and OpenCL to develop a system for analyzing satellite images. this includes a performance benchmarking analysis between traditional and parallel implementations. the proposed system has the potential to be time and energy efficient while giving scientists, planners, and decision-makers access to a variety of valuable data for effective policy and decision-making. Change detection in satellite images is a key application area of the proposed system. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Digital storage

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Exploring the Design Space for Message-Driven Systems for Dynamic Graph processing Using CCA 15th

Exploring the Design Space for Message-Driven Systems for...

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15th international conference on parallel processing and applied mathematics, PPAM 2024

作者： Chandio, Bibrak Qamar Brodowicz, Maciej Sterling, thomas Department of Intelligent Systems Engineering Indiana University Bloomington Bloomington United States

ISBN: (纸本)9783031856969

Computer systems that have been successfully deployed for dense regular workloads fall short of achieving scalability and efficiency when applied to irregular and dynamic graph applications. Conventional computing systems rely heavily on static, regular, numeric intensive computations while High Performance Computing systems executing parallel graph applications exhibit little locality, spatial or temporal, and are fine-grained and memory intensive. With the strong interest in AI which depend on these very different use cases combined with the end of Moore’s Law at nanoscale, dramatic alternatives in architecture and underlying execution models are required. this paper identifies an innovative non-von Neumann architecture, Continuum Computer Architecture (CCA), that redefines the nature of computing structures to yield powerful innovations in computational methods to deliver a new generation of highly parallel hardware architecture. CCA reflects a genus of highly parallel architectures that while varying in specific quantities (e.g., memory blocks), share a multiple of attributes not found in typical von Neumann machines. Among these are memory-centric components, message-driven asynchronous flow control, and lightweight out-of-order execution across a global name space. Together these innovative non-von Neumann architectural properties guided by a new original execution model will deliver the new future path for extending beyond the von Neumann model. this paper documents a series of interrelated experiments that together establish future directions for next generation non-von Neumann architectures, especially for graph processing. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： parallel architectures

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parallel Implementation of Neural Networks for Solving the Problem of Oil Production 8

Parallel Implementation of Neural Networks for Solving the P...

引用

8th international conference on Digital Technologies in Education, Science and Industry, DTESI 2023

作者： Mukhanbet, Aksultan A. Matkerim, Bazargul Al-Farabi Kazakh National University 71 Al-Farabi Avenue Almaty050040 Kazakhstan

Oil production is a pressing challenge in the modern energy sector. Artificial intelligence and neural networks are widely used to enhance the efficiency of the oil and gas extraction processes. However, processing large volumes of data related to oil production requires the efficient parallel implementation of machine learning algorithms. this research addresses the issue of parallel implementation of neural networks for solving oil production tasks. We used data-level parallelism, splitting, and processing in parallel. In addition, parallelism was employed to distribute the training across multiple nodes (processes) and gather the training results. For this purpose, a dataset was created using the Buckley-Leverett model, which allowed us to obtain extensive data on oil reservoirs. the parallel implementation of machine-learning algorithms significantly accelerates the training process of neural networks and enhances the accuracy of their data analysis in oil production. Our work makes a significant contribution to optimizing the oil extraction industry and demonstrates the successful application of parallel data processing in solving complex tasks in this field. MPI technology was used for parallelization, resulting in a twofold acceleration time. the accuracy of the neural network is 98%. © 2023 Copyright for this paper by its authors.

关键词： Extraction

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PQMPV: parallel and Quantified Dense Stereo Disparity Estimation Based on Multi-Path Viterbi 8

PQMPV: Parallel and Quantified Dense Stereo Disparity Estima...

引用

8th IEEE international conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Gu, Rongqi Wang, Tianhang Zou, Tianpei Zhang, Bo Li, Zhijun Zhang, Haotian Chen, Guang Tongji University Department of Automotive Engineering Shanghai China Westwell-lab Shanghai China Tongji-Westwell Driverless Commercial Joint Laboratory Shanghai China Tongji University Department of Computer Science and Technology Shanghai China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China University of Science and Technology of China Department of Automation Hefei China

ISBN: (纸本)9798350300178

Stereo depth estimation plays a crucial role in enabling robots, autonomous driving and other applications. As an ill-posed problem, both deep learning based and traditional methods have been extensively studied in recent years. Traditional methods mainly focus on feature matching between multiple images to estimate depth, but often result in blank pixels with zero disparity and also require significant computation time. In this paper, we propose a new stereo disparity estimation algorithm based on the dynamic programming method known as Viterbi. Our approach optimize the range of disparity calculation through image pyramid, combined with Viterbi algorithm for cost aggregation, and accelerates several calculation steps through parallel computing techniques. Additionally, we improve data transmission and processing speed by quantifying data from float to integer. Experiments on the KITTI dataset and MiddEval benchmark demonstrate that our algorithm achieves significant improvements in average error rate and processing speed of disparity map, making it a promising solution for stereo depth estimation in practical applications. © 2023 IEEE.

关键词： Benchmarking

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