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On Quantum-Assisted LDPC Decoding Augmented with Classical Post-processing 14th

On Quantum-Assisted LDPC Decoding Augmented with Classical ...

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14th international conference on parallel processing and applied mathematics, PPAM 2022

作者： Das Sarma, Aditya Majumder, Utso Vaidya, Vishnu Chandra, M Girish Kumar, A Anil Pramanik, Sayantan Jadavpur University Kolkata India TCS Incubation Bengaluru India TCS Research Bengaluru India

ISBN: (纸本)9783031304446

Utilizing present and futuristic Quantum Computers to solve difficult problems in different domains has become one of the main endeavors at this moment. Of course, in arriving at the requisite solution both quantum and classical computers work in conjunction. With the continued popularity of Low Density Parity Check (LDPC) codes and hence their decoding, this paper looks into the latter as a Quadratic Unconstrained Binary Optimization (QUBO) and utilized D-Wave 2000Q Quantum Annealer to solve it. the outputs from the Annealer are classically post-processed using simple minimum distance decoding to further improve the performance. We evaluated and compared this implementation against the decoding performance obtained using Simulated Annealing (SA) and belief propagation (BP) decoding with classical computers. the results show that implementations of annealing (both simulated and quantum) are superior to BP decoding and suggest that the advantage becomes more prominent as block lengths increase. Reduced Bit Error Rate (BER) and Frame Error Rate (FER) are observed for simulated annealing and quantum annealing, at useful SNR range - a trend that persists for various codeword lengths. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Simulated annealing

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processing of Idiopathic Pulmonary Fibrosis images based on spatial interpolation using DFT, FFT, DCT and LPF

Processing of Idiopathic Pulmonary Fibrosis images based on ...

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international conference on mathematics and Computers in Sciences and in Industry (MCSI)

作者： Irla Mantilla Mihael Arce Universidad Nacional de Ingeniería Av. Túpac Amaru 210 Rímac Perú

the work focuses on the study of existing issues with some medical images obtained from patients with Idiopathic Pulmonary Fibrosis (IPF) who have survived this COVID-19 pandemic. this study analyzes potential causes of incorrect medical diagnoses with this disease. In this regard, we employ numerical algorithms such as DFT (Discrete Fourier Transform), FFT (Fast Fourier Transform), DCT (Discrete Cosine Transform), and LPF (Low-pass filter). the main objective of this work is to demonstrate that with these numerical algorithms based on Continuous and Discrete Fourier theory, it is possible to filter existing noise in IPF radiography images. Furthermore, it is possible to compress, enhance, and improve their resolution so that better decisions can be made in a medical protocol. In this way, it contributes to the understanding of the true images that would be used for an optimal medical diagnosis.

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Detection And Discrimination Of Cracked Digitized Paintings Based On Image processing Methodology

Detection And Discrimination Of Cracked Digitized Paintings ...

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IEEE international conference on Engineering Technologies and applied Sciences (ICETAS)

作者： Nawafil Abdulwahab Amina Shaikh Asadullah Shah Ghulam Mahdi Ali Raza Rang Department of Compute Science International Islamic University Malaysia Kuala lumpor Malaysia Department of Information and Technology International Islamic University Malaysia Kuala Lumpor Malaysia Kimberly Clark Corporation Roswell GA USA United States University of Sufism and Modern Sciences Pakistan

With the passage of time, paintings can be damaged, and common deteriorations found in ancient paintings include cracking. Cracks can be caused by many factors, such as ageing, drying, and mechanical factors. the detection and restoration of crack formation on the earliest digitized paint surface concede great significance and safety for cultural heritages. particular, this paper is based on image processing methodology to detect and discriminate cracks. First, images are enhanced in the preprocessing stage for further processing. then two proposed algorithms are employed to detect and separate medium and thin crack images. the experiments show better results compared with previous work. this study also confirms that the proposed image processing algorithms are an efficient and robust tool for the detection and discrimination of cracks.

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Evolution of Configuration Data in CGP Format Using parallel GA on Embryonic Fabric 13th

Evolution of Configuration Data in CGP Format Using Parall...

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13th international conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2022, and 12th World Congress on Information and Communication Technologies, WICT 2022

作者： Malhotra, Gayatri Duraiswamy, Punithavathi Kishore, J.K. U R Rao Satellite Centre Bangalore India M S Ramaiah University of Applied Sciences Bangalore India

ISBN: (纸本)9783031274985

Digital circuit configuration data can be optimized in the design space using genetic algorithms (GA). Further development of Cartesian Genetic Programming (CGP) has been made to better express data on circuit configuration. In order to realize digital circuits with the potential for self-repair with the least amount of resources, the embryonic fabric architecture has recently arisen. In this study, PHsClone (parallel Half-Sibling and Clone) GA is designed and implemented for evolving configuration data in CGP format for digital circuits built on embryonic fabric architecture. Configuration data or prospective circuit solutions can be generated more quickly using parallel processing on an FPGA. the Xilinx Virtex-7 is used to implement the planned PHsClone GA architecture. the PHsClone technique was validated using well-known benchmark circuits, including a safe mode detection circuit used in flight avionics, a 1-bit adder, a 2-bit comparator for creating 4-bit adder and 8-bit comparator circuits. According to the simulation results, four concurrent PHsClone GA executions (four parallel threads) achieve convergence for the safe mode detection circuit 37 times quicker than a single HsClone GA, 10 times faster for a 1-bit adder, and 3 times faster for a 2-bit comparator. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Genetic algorithms

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parallel processing of radio signals and detector arrays in CORSIKA 8 38

Parallel processing of radio signals and detector arrays in ...

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38th international Cosmic Ray conference, ICRC 2023

作者： Alves, A. Augusto Karastathis, Nikolaos Huege, Tim Alameddine, J.M. Albrecht, J. Alvarez-Muñiz, J. Ammerman-Yebra, J. Arrabito, L. Augscheller, J. Alves, A.A. Baack, D. Bernlöhr, K. Bleicher, M. Coleman, A. Dembinski, H. Elsässer, D. Engel, R. Ferrari, A. Gaudu, C. Glaser, C. Heck, D. Hu, F. Huege, T. Kampert, K.H. Karastathis, N. Latif, U.A. Mei, H. Nellen, L. Pierog, T. Prechelt, R. Reininghaus, M. Rhode, W. Riehn, F. Sackel, M. Sala, P. Sampathkumar, P. Sandrock, A. Soedingrekso, J. Ulrich, R. Xu, D. Zas, E. Karlsruhe Institute of Technology Karlsruhe Germany Astrophysical Institute Vrije Universiteit Brussel Belgium Department of Physics Dortmund Germany Santiago de Compostela Spain Laboratoire Univers et Particules de Montpellier Université de Montpellier Montpellier France Karlsruhe Germany Heidelberg Germany Goethe-Universität Frankfurt am Main Institut für Theoretische Physik Frankfurt am Main Germany Uppsala University Department of Physics and Astronomy Uppsala Sweden Bergische Universität Wuppertal Department of Physics Wuppertal Germany School of Physics Beijing China Vrije Universiteit Brussel Astrophysical Institute Brussels Belgium Brussels Belgium Shanghai Jiao Tong University Shanghai China Instituto de Ciencias Nucleares D.F. México Mexico University of Hawai’i at Manoa Department of Physics and Astronomy Honolulu United States Karlsruhe Germany Lisboa Portugal

this contribution describes some recent advances in the parallelization of the generation and processing of radio signals emitted by particle showers in CORSIKA 8. CORSIKA 8 is a Monte Carlo simulation framework for modeling ultra-high energy particle cascades in astroparticle physics. the aspects associated with the generation and processing of radio signals in antennas arrays are reviewed, focusing on the key design opportunities and constraints for deployment of multiple threads on such calculations. the audience is also introduced to Gyges, a lightweight, header-only and flexible multithread self-adaptive scheduler written compliant with C++17 and C++20, which is used to distribute and manage the worker computer threads during the parallel calculations. Finally, performance and scalability measurements are provided and the integration into CORSIKA 8 is commented. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： C++ (programming language)

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Human Pose Estimation Based on Multi-Level Feature Fusion

Human Pose Estimation Based on Multi-Level Feature Fusion

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international conference on Vision, Image and Signal processing (ICVISP)

作者： Hewei Yu Zhuoheng Li Yanhua Mou Guangzhou Xinhua University Dongguan China South China University of Technology Guangzhou China Liuzhou Institute of Technology Liuzhou China

ISBN: (数字)9798331541460

ISBN: (纸本)9798331541477

We propose a human pose estimation algorithm based on multi-level feature fusion module. To enhance information transmission and feature fusion among different feature levels, we design a multi-level feature fusion structure. Further more, we use a multi-level feature fusion module based on a parallel multi-level feature fusion structure to improve the estimation network's ability to process multi-scale targets. the new network, built upon stacked multi-level feature fusion modules, exhibits strong capabilities in learning semantic information, extracting and fusing multi-scale features. When applied to human pose estimation tasks, it can effectively generate high-precision, high-resolution heatmaps for predicting human key points. this algorithm improves the AP(Average Precision) by 1.3 compared to Simple Baselines on the COCO dataset and enhances the PCKh@0.5 metric by 0.2 compared to Simple Baselines on the MPII dataset. the experiments demonstrate the effectiveness of the proposed algorithm.

关键词： Measurement Heating systems Pose estimation Semantics Neural networks Signal processing algorithms Information processing Feature extraction Prediction algorithms Resource management

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Cardiac Medical Image Segmentation Based on parallel Fusion Network Architecture

Cardiac Medical Image Segmentation Based on Parallel Fusion ...

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Communication, Image and Signal processing (CCISP), international conference on

作者： Wenhao Zhang Jingkun Mao Lin Chen Kun Liu Fengxi Li School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China School of Artificial Intelligence Hebei University of Technology Tianjin China

Cardiovascular disease is the leading cause of death worldwide. Accurate segmentation of cardiac images is able to assist physicians in quantifying and locating abnormal regions and cells in the heart, facilitating diagnosis and treatment and consequently reducing cardiovascular death rate. Semantic segmentation models have been widely used for this task in recent years. However, the task is challenging due to the complex anatomy of the heart and the presence of noise and variations in grayscale in cardiac medical images, which require high segmentation accuracy. To address this challenge, a feature-enhancement model based on Vision-Transformer-Unet (VIT-Unet) is proposed. Specifically, a parallel network that consists of Convolutional Neural Networks (CNNs) and Win-Transformer modules with windowed attention is constructed to extract comprehensive features. then, a Fusion Convolution Transformer is added to enable the integration of global and local features from the parallel network. Finally, the Transformer module in the baseline model is replaced with our parallel fusion feature extraction network. the method proposed in the paper not only achieves higher segmentation accuracy but also presents more robust results compared to the baseline model, as evidenced by the experimental findings.

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Research on Automatic Recognition of Metaphorical Sentence Types in Modern Chinese 22

Research on Automatic Recognition of Metaphorical Sentence T...

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8th international conference on e-Society, e-Learning and e-Technologies, ICSLT 2022

作者： Li, Chunhong Li, Yongquan College of Chinese Language and Culture Jinan University Guangzhou China

ISBN: (纸本)9781450396660

this paper presents work in progress towards automatic recognition of metaphorical sentence types in modern Chinese. We propose an approach to comparison recognition through the use of the experimental design, according to data sampling method, and the experimental data model of CNN, RNN, Transform, Fast Text, Bert base. Keeping in mind the characteristics of Chinese metaphorical sentence, the method is suitable and available for automatic recognition of metaphorical sentence types in modern Chinese, and the Bert base has the highest accuracy. this research contributes to Chinese natural language processing and can be applied in the fields of automatic composition correction, text classification, text summarization, automatic writing and so on. It is of great significance to Chinese text information and formal features, as well as the related process of human-computer communication. © 2022 Association for Computing Machinery.

关键词： Text processing

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Integrated Patient Care Optimization Model: A Novel Model to Enhancing Medical Alliance Efficiency 8th

Integrated Patient Care Optimization Model: A Novel Model to...

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8th international conference on Data Mining and Big Data, DMBD 2023

作者： Wang, Hong Li, Xinyu Ou, Xiaolong Su, Yaofa Zhang, Zhifu College of Management Shenzhen University Shenzhen518060 China Greater Bay Area International Institute for Innovation Shenzhen University Shenzhen518060 China Department of General Practice Shenzhen Longhua People’s Hospital Shenzhen518109 China

ISBN: (纸本)9789819708437

the traditional hierarchical medical system often ignores the linkage among primary medical institutions, and there are still problems such as low patient satisfaction and high hospital operating costs to solve. therefore, in this study, a new medical alliance model, named the Integrated Patient Care Optimization Model (abbreviated as IPCOM) is proposed, in which a new "parallel referral" mechanism is designed and combined with a "two-way referral" mechanism to enhance the linkage among primary medical institutions and their information communications between large hospitals. Additionally, two objectives (i.e. minimization of the patient costs and hospital costs) are considered in the model, simultaneously. As those two objectives conflict with each other, a well-known evolutionary algorithm named NSGA-II (nondominated sorting genetic algorithm) is employed to obtain the Pareto optimal solutions. Furthermore, to verify the validity of the IPCOM, a simulation model is constructed and compared with the real data provided by a medical alliance in Shenzhen. Numerical experiment results demonstrate that the IPCOM performs better than the traditional model in cost saving, and the simulation results fit well with the real data. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multiobjective optimization

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Highly Accurate Scrambled Stochastic Approaches for Multidimensional Sensitivity Analysis in Air Pollution Modeling 9th

Highly Accurate Scrambled Stochastic Approaches for Multidi...

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9th international conference on New Trends of the Applications of Differential Equations in Sciences, NTADES 2022

作者： Todorov, Venelin Georgiev, Slavi Department of Information Modeling Institute of Mathematics and Informatics Bulgarian Academy of Sciences Acad. Georgi Bonchev Str. Block 8 Sofia1113 Bulgaria Department of Parallel Algorithms Institute of Information and Communication Technologies Bulgarian Academy of Sciences Acad. Georgi Bonchev Str. Block 25A 1113 Sofia Bulgaria Department of Applied Mathematics and Statistics Faculty of Natural Sciences and Education University of Ruse 8 Studentska Str. Ruse7004 Bulgaria

ISBN: (纸本)9783031214837

A thorough experimental investigation of Monte Carlo algorithms based on Halton and Sobol scrambling algorithms has been performed for the first time for the model under consideration. For scrambling Halton sequence, we use a permutation of the radical inverse coefficients derived by applying a reverse-radix operation to all of the possible coefficient values. For scrambling Sobol sequence, we use random linear scramble combined with a random digital shift. these methods have never been applied and compared before for the Unified Danish Eulerian model and this motivates our study. the novelty of the proposed approaches is that Halton scrambling algorithm has been applied for the first time to sensitivity studies of the particular air pollution model. the computational experiments demonstrate that the proposed stochastic approaches are efficient for the considered multidimensional integrals evaluation and especially for computing small by value sensitivity indices which are very important for the reliability of the mathematical model. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Sensitivity analysis

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