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SAFA 2024 - Proceedings of the 5th International Workshop on Systems and algorithms for Formal Argumentation, co-located with 10th International conference on Computational Models of Argument, COMMA 2024

SAFA 2024 - Proceedings of the 5th International Workshop on...

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5th International Workshop on Systems and algorithms for Formal Argumentation, SAFA 2024

the proceedings contain 10 papers. the topics discussed include: reasoning in structured argumentation: assumption-based argumentation and ASPIC+;on computational problems for infinite argumentation frameworks: classifying complexity via computability;on diagnostic arguments in abstract argumentation;splitting argumentation frameworks with collective attacks;fantastic argumentation tools and where to find them;an evaluation of algorithms for strong admissibility;effects of graph neural network aggregation functions on generalizability for solving abstract argumentation semantics;and a sequent calculus representation of Lorenzen dialogue extended with why-because dialogue.

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Reduce Deblurring Generative Networks Training complexity with Encoder-Decoder Model 5

Reduce Deblurring Generative Networks Training Complexity wi...

引用

5th International conference on Artificial Intelligence and Electromechanical Automation, AIEA 2024

作者： Cheng, Jiangmai Jiang, Bo Xu, Hong The 32nd Research Institute of China Electronics Technology Group Corporation Shanghai China

ISBN: (纸本)9798350366174

We propose a deblurring method that integrates a combination of Generative Adversarial Networks (GANs) and encoder-decoder models. Our approach offers higher efficiency and reduced training complexity compared to generative deblurring models which utilizing GANs as the backbone network. In this approach, we employ the encoder as the feature extraction module, and then passes the features to the GANs for deblurring, followed by image reconstruction using the decoder as the last module. To ensure image fidelity, skip connections are introduced between the encoder and decoder. Meanwhile, we introduce a targeted training methodology designed to mitigate fluctuations in network parameters, thereby maximizing the efficacy of the model's training velocity. We additionally conducted comparative evaluations based on the GoPro and Kohler datasets, contrasting our model against previously proposed algorithms to approve its exceptional performance in deblurring efficacy and efficiency. © 2024 IEEE.

关键词： Generative adversarial networks

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A Regression-Based Optimal Scaling Factor Scheme for 5G LDPC Codes with MIMO Systems 5

A Regression-Based Optimal Scaling Factor Scheme for 5G LDPC...

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5th IEEE International conference on Emerging Trends in Electrical, Electronic and Communications Engineering, ELECOM 2024

作者： Indoonundon, Madhavsingh Fowdur, Tulsi Pawan University of Mauritius Department of Electrical and Electronic Engineering Réduit Mauritius

ISBN: (纸本)9798331532475

Low-Density Parity Check (LDPC) codes are powerful forward error correction (FEC) codes which achieve near-channel capacity performances. they have been adopted in several technologies, such as WiFi and 5G NR, and there is active research on optimising both their encoding and decoding algorithms. this paper proposes a low-complexity regression-based optimal scaling factor (OSF) scheme to optimise the Normalized Min-Sum Algorithm (NMSA) performance in 5G NR with different Multiple-Input Multiple-Output (MIMO) configurations. the proposed scheme provides Eb/N0 gains in all tested scenarios, with the maximum achievable Eb/N0 gain being 1 dB when using the 8T2R MIMO configuration in the low BER range. © 2024 IEEE.

关键词： Forward error correction

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A Lightweight Human Pose Estimation Algorithm Based on High Resolution Network 5

A Lightweight Human Pose Estimation Algorithm Based on High ...

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5th International conference on Natural Language Processing, ICNLP 2023

作者： Ma, Sai Ge, Haibo He, Wenhao Huang, Chaofeng An, Yu Zhou, Ting Xi'an University of Posts and Telecommunication School of Electronic Engineering Xi'an China

ISBN: (纸本)9798350302219

Human pose estimation is an important research direction in the field of computer vision. At present, the mainstream human pose estimation algorithms have high complexity, large amount of calculation, and cannot be run on resource-constrained devices such as mobile terminals, which severely limits the popularization and application of this technology. Aiming at the problem of increased network model parameters and computational complexity, based on the High-Resolution Network (HRNet), a lightweight human pose estimation network incorporating Ghost module and attention mechanism is proposed. Replaced with Ghost convolution, and added the attention mechanism Concurrent Spatial and Channel Squeeze and Channel Excitation Net module on this basis to ensure the prediction accuracy of the network. Under the same image resolution and environment configuration, the experimental results on the COCO dataset show that the improved network model reduces the number of parameters by 98.3% compared to the high-resolution network model, and reduces the computational complexity by 67.6%. the experimental results show that the improved network model can effectively reduce the amount of network parameters and reduce the computational complexity while maintaining a certain prediction accuracy. © 2023 IEEE.

关键词： Computational complexity

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Improved internal voxelization algorithm based on depth buffer 5

Improved internal voxelization algorithm based on depth buff...

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5th International Academic Exchange conference on Science and Technology Innovation, IAECST 2023

作者： Li, Changhao Liu, Jun Wang, Hongliang Xiu, Pengfei Shenyang University of Chemical Technology Shenyang China Chinese Academy of Sciences University of Chinese Academy of Sciences Liaoning Province Human-Computer Interaction System Engineering Research Center Based on Digital Twin Shenyang Institute of Computing Technology Shenyang China

ISBN: (纸本)9798350357738

Aiming to address the inefficiencies in existing internal voxelization algorithms, a solution has been proposed to use a two-dimensional depth buffer table to record the interval range of surface voxels, reducing the number of internal voxels to be checked. the complexity of this algorithm is independent of the model's complexity. the voxel model is stored using a non-uniformly subdivided octree structure, where if a particular layer's node and all of its child nodes are internal voxels, there is no need for further subdivision, reducing storage space. Experimental results indicate that the improved algorithm can run correctly while achieving better time and space efficiency. © 2023 IEEE.

关键词： Computational complexity

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Neural Network Task Time Mapping of a 3-DOF Clavel's Delta Robot 5th

Neural Network Task Time Mapping of a 3-DOF Clavel's Delta R...

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5th International conference of International-Federation-for-the-Promotion-of-Mechanism-and-Machine-Science IFToMM ITALY (IFIT)

作者： Righettini, Paolo Strada, Roberto Cortinovis, Filippo Univ Bergamo Dept Engn & Appl Sci Viale Marconi 5 I-24044 Dalmine Italy

ISBN: (纸本)9783031645556;9783031645532;9783031645525

the throughput of robotized pick and place cells can be improved by scheduling algorithms that determine optimal task sequences using estimates of the robot's cycle times;the latter however depend on factors such as the robot's dynamics, the motion planning algorithm, and the specific configuration of the task, which is often not known in advance. Exact evaluation of the task times is therefore a computationally expensive procedure that should be performed as sparingly as possible during real time calculations. In this paper a recently developed architecture for the efficient approximation of a manipulator's task times is applied to a 3-DOF Clavel's Delta robot. Such an architecture is composed of a dynamic and kinematic model of the robot, of an optimizing motion planner, and of a neural network able predict the task times quickly enough to be used in online process-optimizing scheduling algorithms.

关键词： robot process optimization real-time task scheduling AI in robotics

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A Key Generation Algorithm for Cryptographic algorithms to Improve Key complexity and Efficiency 5

A Key Generation Algorithm for Cryptographic Algorithms to I...

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5th International conference on Smart Systems and Inventive Technology, ICSSIT 2023

作者： Umapathy, B. Kalpana, G. Srm Institute of Science and Technology College of Science and Humanities Department of Computer Science Kattankulathur Tamil Nadu Chennai603203 India

ISBN: (纸本)9781665474672

In the recent days people use a variety of online software applications to move data from one location to another. To secure personal data from hackers, software or applications use cryptographicbased algorithms. the encryption and decryption processes are the foundation of the cryptographic algorithm, which will be carried out with the help of a key. Cryptographic algorithms employ automatic key generation that starts with the user's password, whereas another generating key directly interprets the password. A symmetric algorithm uses the same key for both encryption and decryption. For key generation, symmetric algorithms use a second or subsidiary method. the password is protected using this key generation process from various key attacks. the key generation algorithm functions as an interpreter, transforming a password from a human-readable form to a machine-readable form. An increase in permutations and combinations helps to protect the password;additional characteristics are being added to the algorithm. To get around the restricted key bit size, this paper proposed the KEY SECURE-KEY (KSKEY) algorithm. However, increasing the key size is not a suitable way to encrypt data because multi-core processors in modern microprocessors are significantly increasing processingspeed. © 2023 IEEE.

关键词： Cryptography

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Unraveling Genetic complexity: Fine-tuning Machine Learning Models for DNA Sequence Analysis with K-mer Size 5

Unraveling Genetic Complexity: Fine-tuning Machine Learning ...

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5th International conference on Cybernetics and Intelligent Systems, ICORIS 2023

作者： Lukman Adnyana, I Made Anggar Dwi Purnama, Fajar Latumakulita, Luther Alexander Rosalia, Ayang Armelita Pawana, I Wayan Adi Juliawan Indonesia University of Education Dept. of Marine Information System Bandung Indonesia Udayana University Dept. of Electrical Engineering Denpasar Indonesia Udayana University Dept. of Information Technology Denpasar Indonesia Sam Ratulangi University Dept. of Information System Manado Indonesia

ISBN: (纸本)9798350369489

In the realm of genetic analysis, the utilization of machine learning models holds great potential for unraveling the intricate complexities of DNA sequence data. this study aims to address the pressing need for advanced DNA sequence analysis methods by leveraging K-mer representations and fine-tuning machine learning algorithms to achieve optimal performance. By elucidating the reasons behind the study and highlighting the significance of these approaches, this research contributes to the broader understanding of DNA sequence intricacies. © 2023 IEEE.

关键词： DNA sequences

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Low-complexity equalization algorithm for orthogonal time frequency space based on iterative enhancement 5

Low-complexity equalization algorithm for orthogonal time fr...

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5th International conference on Computer Communication and Network Security, CCNS 2024

作者： Wei, Zhaochuan Wang, Jiawei Peng, Ming Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin University of Electronic Technology Guilin541004 China National-Local Joint Engineering Research Center of Satellite Navigation Positioning and Location Services Guilin University of Electronic Technology Guilin541004 China School of Information and Communication Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9781510681842

Orthogonal Time Frequency Space (OTFS) modulation technology can effectively address the significant challenges brought by fast time-varying channels to signal detection at the receiver, thus providing reliable system transmission performance for high-mobility communication environments. To tackle the problem of high complexity in common OTFS receiver signal detection algorithms, we propose an iterative enhanced detection algorithm based on the delay-time domain. In the delay-time domain, the channel sub-matrix exhibits diagonal characteristics, and the transmission signal and channel matrix appear in the form of vector dot products, effectively reducing the complexity of the receiver signal detection algorithm design. Based on this property, simultaneous utilization of iterative enhanced detection method is employed for interference elimination and Maximum Ratio Combining (MRC) estimation symbol of Least Square Minimum Residual (LSMR) equalizer, aiming to obtain channel delay multipath diversity gain and reduce detector computational complexity. Simulation analysis results demonstrate that compared to standard OTFS signal detection algorithms, such as Minimum Mean Square Error (MMSE) and Message Passing (MP), this detection scheme exhibits certain advantages in terms of computational complexity and system demodulation performance. © 2024 SPIE.

关键词： Mean square error

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Low-complexity Hermite Nonlinear Filter for Active Noise Control 5

Low-Complexity Hermite Nonlinear Filter for Active Noise Con...

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5th IEEE International conference on Electronic Information and Communication Technology, ICEICT 2022

作者： Lu, Lu Yang, Xiaomin College of Electronics and Information Engineering Sichuan University Chengdu610065 China

ISBN: (数字)9781665472111

ISBN: (纸本)9781665472111

In this article, a class of low-complexity Hermite nonlinear (HN) filters is proposed for nonlinear active noise control (NLANC). the HN filters belong to linear-in-the-parameter (LIP) nonlinear filters, which also have the orthogonal property for white input signals. Based on the HN filters, the fast affine projection algorithm (FAPA) and the dichotomous coordinate descent (DCD) method are introduced, generating DCD-filtered-h FAPA (DCD-FhFAPA). Benefiting from fast recursive filtering and DCD strategies, the computational complexity of the algorithm can be reduced. To further alleviate computational complexity, two methods of discarding redundant data are proposed based on the Mahalanobis distance, leading to the DCD-low-complexity filtered-h FAPA-I (DCD-LFhFAPA-I) and DCD-LFhFAPA-II algorithms. At the price of slightly slow convergence, two new algorithms significantly reduce the computational load for NLANC. Simulation results exhibit the effectiveness of the DCD-FhFAPA, DCD-LFhFAPA-I, and DCD-LFhFAPA-II algorithms. © 2022 IEEE.

关键词： Computational complexity

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