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A Low complexity PAPR Reduction of FMBC-OQAM Systems with Hybrid SLM Technique

A Low Complexity PAPR Reduction of FMBC-OQAM Systems with Hy...

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international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： V. Sudarshani Kataksham P. Siddaiah ECE Dept. ANU College of Engg and Technology Guntur Andhra Pradesh India

the Fifth generation communication systems are relied on filter bank based multi carrier modulation schemes. When Filter Band Multi carrier combined with OQAM it became versatile choice in many of the wireless communication systems. this system draws the attention of many scholars to implement new physical layers and different wireless protocols. FBMC modulation need not require cyclic prefix extension and it displays sophisticated robustness for frequency offsets and it provides orthogonality and it handles larger band widths also. FBMC faces the problems like PAPR in OFDM (Orthogonal Frequency Division Multiplexing). To overcome this problem, Trellis coded based SLM was proposed but this method also suffered with limitation of complexity in huge computation. In this work, a modified low complexity trellis coded SLM approach is presented to minimize the PAPR with low computation cost.

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Efficient Real-Time Dense Pedestrian Detector Based on Improved YOLOv7-tiny 7

Efficient Real-Time Dense Pedestrian Detector Based on Impro...

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7th international conference on Advances in Image Processing, ICAIP 2023

作者： Xuezhi, Li Yiping, Shi Ziyun, Zhao Shaojie, Shi Jin, Liu College of Electronic and Electrical Engineering Shanghai University of Engineering Science China

ISBN: (纸本)9798400708275

the state-of-the-art YOLO framework strikes an excellent balance between speed and accuracy and has become one of the most effective object detection algorithms. However, when performing dense pedestrian detection tasks, the network is computationally intensive, real-time is insufficient, and it is difficult to be applied to edge devices with weak computational power in practical use. therefore, we propose a detection algorithm based on YOLOv7-tiny improvement. Based on the GhostNetv2 network, we use the parameter-free attention mechanism SimAM to construct the GhostNet-tiny structure and propose the C3Ghost-tiny module to be combined with the YOLO network in order to reduce the network computational parameters. We propose a new neck network structure to extract richer information with a bi-directional weighted pyramid structure and weighted connectivity of features at different scales. We also use WIoU as a coordinate loss function to improve the network’s attention to small targets. We tested the effectiveness of the proposed method on the public dataset CrowdHuman, and the results show that our method can effectively reduce the network parameters while improving the accuracy. Notably, compared to the YOLOv7-tiny model, our model improves the accuracy value by 2.13%, reduces the amount of network parameters by 5.9%, reduces the amount of floating-point calculations by 60.3%, reduces the size of the network model file by 27.7%, and improves the detection speed by up to 46.64%. © 2023 Copyright held by the owner/author(s).

关键词： Digital arithmetic

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Design and Implementation of Novel Reversible Full Adder using QCA

Design and Implementation of Novel Reversible Full Adder usi...

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international conference on Computing Methodologies and Communication (ICCMC)

作者： Raj Karwa Shubham Singh Nithin N Yashwant Karekar Rashmi Seethur Department of Electronics and Communication PES University Bangalore India

One of the most well-known nanotechnologies thought to continue the scaling-down theme of sub-micron electronics is quantum-dot-cellular automata. Consequently, employing this new technique, several combinational logic circuits have also been redesigned and put into use. the QCA Full adder cell, which is thought of as the standard structure in designing arithmetic circuits, has received a lot of attention in research seeking to decrease circuit complexity and delay. Here, this study suggests a single-layer reversible structure which uses a total cell count of 121 cells and area of $0.20\mu\mathrm{m}^complexity$ , which shows 47.03% improvement in cell count in comparison to contemporary designs, the complete adder has fewer cells (less complexity), a smaller surface area, and a smaller overall size. the program employed was the QCA designer 2.0.3, which was used to construct and evaluate the functionality of the suggested design. To construct QCA circuit, a multilayer crossovers architecture is not preferred because to the expensive cost and growing circuit complexity.

关键词： Microprocessors Layout Computer architecture Nonhomogeneous media Compressors complexity theory Delays

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Building Disease Prediction Model Using Machine Learning algorithms on Electronic Health Records' Logs 7

Building Disease Prediction Model Using Machine Learning Alg...

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7th international conference on Digital Technologies in Education, Science and Industry, DTESI 2022

作者： Rakhmetulayeva, Sabina Kulbayeva, Aliya International Information Technology University Manas St. 34/1 Almaty Kazakhstan

the number of tasks devoted to predicting the incidence of infectious diseases is growing rapidly due to the availability of statistical data supporting the analysis. this article describes the main solutions currently available for creating short and long-term disease forecasts. their limitations and practical applications are shown. Much attention is given to the Naïve Bayes classification, logistic regression, artificial neural network algorithm and k-means artificial neural networks as methods of model analysis based on machine learning. this article provides an overview of two popular machine learning algorithms used to predict diseases. the standard datasetis used for a wide range of diseases including fungal infection, allergy, GERD, chronic cholestasis, peptic ulcer disease, diabetes, bronchial asthma, migraine, paralysis (brain hemorrhage) and more. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0).

关键词： Neural networks

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Safety Helmet Detection Algorithm Based on Improved YOLOv7

Safety Helmet Detection Algorithm Based on Improved YOLOv7

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IEEE Information Technology, Networking, Electronic and Automation Control conference

作者： Hongtao Deng Min Wang Xun Zhu Liping Zou Can Liu Zhuwei Lin College of Artificial Intelligence Jianghan University WuHan China

ISBN: (数字)9798350370805

ISBN: (纸本)9798350370812

the wearing of helmets is crucial for construction sites, which can protect workers from injuries caused by head impacts and reduce the occurrence of safety accidents. the image size captured by the construction site camera is small, and it is inevitable that there are omissions and wrong detections; considering the complexity of the construction site, there are also the problems of slow detection speed and insufficient detection accuracy, so this paper proposes a helmet detection algorithm based on the improved YOLOv7. the simam module is added to the backbone network of YOLOv7, which makes the model pay more attention to the extraction of main features and reduces the problems of omission and misdetection; based on the NWD method, the loss function is improved to improve the regression accuracy and accelerate the convergence. the experimental results show that the improved algorithm has better results than the original YOLOv7 model by improving the accuracy by 2.1% and mAP by 1.4%.

关键词： Accuracy Head Feature extraction Cameras Safety complexity theory Detection algorithms Information technology Injuries Convergence

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Studying the dynamics and complexity of a 3d laser plasma system 7th

Studying the dynamics and complexity of a 3d laser plasma sy...

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7th international conference on Solid State Science and Technology, ICSSST 2019

作者： Muhammad Firdaus, Abdul Rahim Hayder, Natiq Nur Aisyah, Abdul Fataf Faculty of Defence Science and Technology Universiti Pertahanan Nasional Malaysia Sg. Besi Kuala Lumpur Malaysia Information Technology College Department of Communications Technologies Engineering Imam Ja’afar AlSadiq University Baghdad Iraq Centre for Defence Foundation Studies Universiti Pertahanan Nasional Malaysia Sg. Besi Malaysia Cyber Security Centre Universiti Pertahanan Nasional Malaysia Sg. Besi Malaysia

ISBN: (纸本)9783035735802

In this paper, a 3D laser plasma interaction system is presented, analysed, and implemented. the system has two unstable equilibria, and two types of coexisting attractors in which the coexistence of two periodic orbits and the coexistence of two chaotic attractors can be clearly observed. the multistability behaviours are determined by the bifurcation diagrams, largest Lyapunov exponents, and phase spaces. Moreover, the complexity performance of the laser plasma interaction system is investigated by the contour plot of the Sample Entropy. © 2021 Trans Tech Publications Ltd, Switzerland.

关键词： Differential equations

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Video and Image complexity in Human Action Recognition 7th

Video and Image Complexity in Human Action Recognition

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7th international Workshop on Artificial Intelligence and Pattern Recognition (IWAIPR)

作者： Burgos-Madrigal, Andrea Altamirano-Robles, Leopoldo Natl Inst Astrophys Opt & Elect Comp Sci Puebla Mexico

ISBN: (纸本)9783030896911;9783030896904

We analyze the relation of video complexity with the performance of Human Action Recognition (HAR) algorithms. the rationale behind this is that variations in image conditions (e.g. occlusion, camera movement, resolution, and illumination), and image content (e.g. edge density, and number of objects), both depicting scene complexity increase the difficulty to recognize activities for a computing model. the HAR algorithms used in this work are improved Dense Trajectories (iDT) [25], Motion-Augmented RGB Stream for Action Recognition (MARS) [5], and SlowFast [7] compared with the number of people and objects in the scene and to three statistical measures: entropy, number of regions and edge density. the results so far show a correlation between complexity and the classification performance. Mask-RCNN simulation for counting elements was carried in the supercomputer cluster of LSC-INAOE.

关键词： Video complexity Action recognition Correlation

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Resilient Quantized Consensus in Adversarial Environment Using Trusted Neighbors

Resilient Quantized Consensus in Adversarial Environment Usi...

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Advanced algorithms and Control Engineering (ICAACE), international conference on

作者： Peng Zhang Ziming Luo Sentang Wu School of Automation Science and Electrical Engineering Beihang University Beijing China General Department of Networks and Communications 54th Research Institute of the China Electronics Technology Group Corporation Shijiazhuang China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

this paper addresses the challenge of achieving resilient quantized consensus in multiagent systems operating within adversarial environments. Existing algorithms often rely on an assumption of the maximum adversarial agents in the multiagent systems or neighbors which may be impossible to appropriately estimate in practice. To address this limitation, we propose a novel filtering method that dynamically maintains a trusted neighbor set to identify and filter out suspicious states without requiring knowledge of the maximum adversaries. Additionally, we introduce a distributed resilient quantized control protocol tailored for regular agents, ensuring consensus despite limited communication and memory constraints that enforce agents to adopt integer values. We analyze a graph-theoretic condition that is both necessary and sufficient for our proposed control protocol to succeed. Finally, we validate our theoretical findings through simulations.

关键词： Protocols Parameter estimation Control engineering Filtering Heuristic algorithms Memory management Filtering algorithms

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Color Coding for the Fragment-Based Docking, Design and Equilibrium Statistics of Protein-Binding ssRNAs 28th

Color Coding for the Fragment-Based Docking, Design and Equi...

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28th Annual international conference on Research in Computational Molecular Biology (RECOMB)

作者： Yacoub, Taher Gonzalez-Aleman, Roy Leclerc, Fabrice de Beauchene, Isaure Chauvot Ponty, Yann Inst Polytech Paris LIX CNRS UMR 7161 Palaiseau France Univ Paris Saclay Inst Integrat Biol Cell I2BC UMR 9198 CNRS Gif France Univ La Habana Lab Quim Computac & Teor LQCT Havana Cuba Univ Lorraine UMR 7503 CNRS LORIA Nancy France

ISBN: (纸本)9781071639887;9781071639894

We revisit the fragment-based docking and design of single-stranded RNA aptamers (ssRNAs), consisting of k nucleotides, onto a rigid protein. Fragments, representing short sequences of (modified) nucleotides, are individually docked as poses onto the protein surface using a force field. Compatible poses are then assembled while optimizing for an additive notion of energy, to obtain stable conformations that can either be constrained to represent an input ssRNA sequence (docking) or left unconstrained (design). However, a brute-force enumeration of clash-free conformations quickly becomes prohibitive due to their super-exponential (theta(n(k)) worst-case) combinatorial explosion, hindering the potential of fragment-based methods towards docking and design. In this work, we adapt the color-coding technique, introduced by Alon, Yuster and Zwick, to optimize over self-avoiding fragment assemblies in time/space linear on n the number of poses, and in time only exponential on k the number of fragments. the dynamic programming algorithm at the core of our method is surprisingly simple, and can be extended to produce suboptimal candidates, or modified to perform Boltzmann sampling of candidates assemblies. Using a rejection principle, and further optimized by a clique decomposition of clashing poses, these algorithms can be leveraged into efficient algorithms optimizing over clash-free complexes. the resulting sampling procedure can further be adapted into statistically-consistent estimators for any computable feature of interest. We showcase some of the capabilities of this new framework by reanalyzing a set of 7 documented ssRNA-protein complexes, demonstrating its practical relevance and versatility.

关键词： Fragment-based docking RNA design RNA-protein interaction Parameterized complexity algorithms

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Guiding Grokking: How Curriculum Learning Shapes Algorithmic Understanding in Neural Networks

Guiding Grokking: How Curriculum Learning Shapes Algorithmic...

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Software Engineering and Computer Science (CSECS), international conference on

作者： Haotian Chen Zihao Wang College of Computer Science-College of Software Inner Mongolia University Hohhot China

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

Understanding how neural networks suddenly achieve strong generalization after extended training (grokking) remains a fundamental challenge in deep learning. While this phenomenon has been observed in algorithmic tasks, the factors influencing its emergence remain poorly understood. We investigate whether curriculum learning—gradually increasing task complexity—can facilitate and accelerate grokking. through systematic experiments on modular arithmetic tasks with varying prime moduli, we compare four curriculum strategies (linear, exponential, step-wise, and gradual progression) against a baseline. Our results reveal that only modular addition benefits significantly from curriculum learning, achieving 81.1% validation accuracy with gradual progression compared to 65.7% and 57.2% for linear and exponential curricula respectively. In contrast, operations like modular division and permutation show minimal improvement, with validation accuracies below 20% across all curricula. the gradual curriculum maintains smoother training loss transitions and higher training stability, particularly for addition, while step-wise progression shows the worst performance with validation accuracy drop- ping to 34.4% for addition. these findings suggest curriculum learning is most effective for operations with simpler underlying structures, while complex operations remain challenging regardless of curriculum design. this work provides practical insights into curriculum strategies for algorithmic learning tasks and highlights fundamental limitations of current approaches.

关键词： Training Deep learning Computer science Accuracy Systematics Shape Software algorithms Neural networks complexity theory Software engineering

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