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Overcoming complexity of (Cyber) war: the logic of useful fiction in cyber exercises scenarios 5

Overcoming complexity of (Cyber) war: The logic of useful fi...

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5th italian conference on Cybersecurity, ITASEC 2021

作者： Di Feo, Marzio

the paper is an attempt to analyze the logic and the impact of "useful fiction" (or "fictional intelligence") in cyber exercises scenarios as an approach to prepare for future conflicts. Cyberspace increased the complexity of war phenomenon with its characteristics of artificiality, plasticity, and uncertainty. To overcome this complexity, cyber warriors need to adapt to everchanging scenarios. In this view, the development of a new epistemology of wargaming and cyber exercises could provide a deeper understanding of war and, thus, enhance the capability to cope with this instability. In this framework, fictional intelligence would enrich the research of (un)imaginable phenomena to prevent future threats. © 2020 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Computer circuits

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Dual-LightGCN+: Enhanced Dual Light Graph Convolutional Network for Discriminative Recommendation

Dual-LightGCN+: Enhanced Dual Light Graph Convolutional Netw...

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Consumer Electronics and Computer Engineering (ICCECE), 2021 IEEE International conference on

作者： Zhidong Xie Ning Zhang School of Computer Science and Technology Dongguan University of Technology Dongguan China

ISBN: (数字)9798331533113

ISBN: (纸本)9798331533120

the Dual-LightGCN has shown promise in recommendation systems but faces limitations in explicitly modeling similarity signals between users and items, which restricts its ability to uncover potential relationships and negatively impacts recommendation performance. To address this, we propose an enhanced approach, Dual-LightGCN+ (DLGN+), which introduces edges between two-hop neighbors in the original user-item interaction graph to construct user-user and item-item graphs. this modification allows for more effective capture of similarity signals. Furthermore, we employ a sampling strategy that retains the maximum spanning tree of these newly constructed graphs, balancing the trade-off between information preservation and computational cost. this strategy substantially reduces both space and time complexity by selectively maintaining the most relevant similarity information. We evaluated DLGN+ on two datasets of varying sizes and compared it with several state-of-the-art recommendation algorithms. Experimental results demonstrate that DLGN+ outperforms the widely used methods in recommendation accuracy.

关键词： Graph convolutional networks Convolution Computational modeling Scalability Neural networks Robustness Computational efficiency Time complexity Recommender systems Faces

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AI Driven Innovation for Boosting Performance and efficiency in Mobile and Wireless Networks

AI Driven Innovation for Boosting Performance and efficiency...

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Communications, Information, Electronic and Energy Systems (CIEES), International conference on

作者： Arjola Biti Olimpjon Shurdi Luan Ruci Dept. of Electronics and Telecommunications Faculty of Information Technology Polytechnic University of Tirana Tirana Albania RAN Department Espo Nokia Oslo Norway

ISBN: (数字)9798350352863

ISBN: (纸本)9798350352870

the escalating complexity and data volume in today’s digital networks demands innovative strategies to enhance performance and efficiency. this survey explores the possibilities of optimization techniques powered by AI to address this critical need. By utilizing artificial intelligence (AI) algorithms, including machine learning and deep learning, the study explores how AI can transform network optimization and management, to achieve superior performance and reliability. the investigation focuses on how AI algorithms can process extensive network data, recognize patterns, and make informed decisions to enhance network configurations and resource allocation methods. the review highlights key findings and insights, emphasizing the revolutionary impact of AI-based optimization for improving network performance and efficiency. It focuses on the advantages of AI-based methods in power control and EE efficiency, resource allocations, user connection, intelligent beam management, and channel estimation, by automating optimization processes, minimizing operational costs, and flexibly adjusting to evolving network conditions and user requirements. Furthermore, the review addresses the concerns and aspects associated with implementing AI-driven optimization techniques. In conclusion, the review underscores the crucial role of AI-driven optimization in tackling the growing complexities of network optimizations. It advocates for continuous exploration and innovation initiatives to fully harness the potential of AI-driven optimization, unlocking enhanced performance and operational efficiency in network systems.

关键词： Deep learning Technological innovation Machine learning algorithms Reviews Wireless networks Heuristic algorithms complexity theory Resource management Reliability Optimization

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Colored Token Swapping Using Broom

Colored Token Swapping Using Broom

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Global conference for Advancement in Technology (GCAT)

作者： Ajila L Indulekha T S G Anuja Department of Computer Science and Applications Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri Kerala India

ISBN: (数字)9798350376685

ISBN: (纸本)9798350376692

Token swapping, a fundamental problem in computational graph theory involves rearranging tokens at graph vertices through minimal swaps to achieve a desired configuration. this problem finds applications in various fields, including task scheduling, DNA rearrangement, and network reconfiguration. A well-established variant, colored token swapping, assigns distinct colors to tokens residing on vertices in a graph. the complexity of token swapping is NP-hard. Two-colored token swapping is a specific case where there are only two distinct colors for the tokens. this work introduces a novel, efficient algorithm for swapping two-colored tokens on a specific tree called a single broom, achieving a configuration where each token resides in its designated position. Single brooms are constructed by attaching the center vertex of a star(the vertex with degree n-2) to one of the leaf nodes of a path. the suggested algorithm utilizes the inherent properties of the tree structure to streamline the necessary swaps for achieving the desired configuration.

关键词： Processor scheduling DNA Color Transforms Graph theory complexity theory Classification algorithms Telecommunications Robots Sorting

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An Improved Mobilenetv3-Yolov5 Infrared Target Detection Algorithm Based on Attention Distillation 5th

An Improved Mobilenetv3-Yolov5 Infrared Target Detection Alg...

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5th EAI International conference on Advanced Hybrid Information Processing (ADHIP)

作者： Jin, Ronglu Xu, Yidong Xue, Wei Li, Beiming Yang, Yingwei Chen, Wenjian Harbin Engn Univ Coll Informat & Commun Engn Harbin 150001 Peoples R China Harbin Engn Univ Coll Underwater Acoust Engn Harbin 150001 Peoples R China

ISBN: (纸本)9783030945510;9783030945503

Most current target detection algorithms have problems such as high computational complexity and poor adaptability, which are difficult to meet actual application requirements and are deployed on mobile embedded platform devices. Towards solving the above problems, in this paper, we propose an improved Mobilenetv3-Yolov5 infrared target detection algorithm based on attention distillation. Firstly, the improved Mobilenetv3 and Recurrent FPN-PAN are suitable for reconstruction of the Yolov5 model. Secondly, Attention Distillation is employed to improve the accuracy in object detection. Further, that there doesn't exist public dataset in the field of security infrared target detection, this paper constructs an infrared image dataset (coming soon) that contains a variety of scenarios with pedestrians, motor vehicles, and non motorized targets. Experimental results of tests conducted on the above dataset show that compared with original Yolov5, the proposed algorithm has the following improvements: (1) 88.2% smaller with the model size as only 3.5 MB;(2) 2 times faster with 60.27;(3) 73.9% lower complexity with 4.7 GFLOPS;and (4) 0.8 accuracy higher with 92.1 overall mAP. the testing results on Ambarella platform show that our model achieves higher accuracy and faster running speed with 91.9 mAP and 32.48 FPS, which is 0.9 higher than Yolov5, 3.4 higher than Yolov3-SPP, 6.8 higher than Yolov3, 25 higher than Yolov2, 17.6 higher than FasterR-CNN, in terms of accuracy.

关键词： Improved Mobilenetv3 Recurrent FPN-PAN Attention distillation

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Research on lightweight algorithm for smoking detection based on improved YOLOv8

Research on lightweight algorithm for smoking detection base...

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Electronic Communication and Artificial Intelligence (IWECAI), International Workshop on

作者： Guorui Zhou Xingjian Wang Northeast Forestry University College of Computer And Control Engineering Harbin China

ISBN: (数字)9798350386943

ISBN: (纸本)9798350386950

In response to the issues of high computation and large model parameters in current smoking detection algorithms, making them difficult to deploy on edge devices, this paper proposes an improved lightweight YOLOv8 algorithm for real-time detection and accurate recognition of smoking targets. Firstly, the C2f module in the backbone of YOLOv8 is replaced with a lightweight ContextGuided module, which enhances the accuracy of small object detection through the analysis of feature context, and also reduces model complexity. Secondly, a slim-neck structure paradigm is adopted to further optimize the complexity of the neck part without affecting accuracy. Experimental results show that the improved algorithm reduces the number of parameters, computation, and model size by 17.94%, 20.990%, and 15.78 % , respectively, with mAP@0.5 and FPS reaching 94.9% and 98. this ensures real-time and reliable detection.

关键词： Accuracy Target recognition Computational modeling Feature extraction Real-time systems complexity theory Neck

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Design Of A Framework For Optimizing Bandwidth Allocation Of Video In Wireless Networks Using Hybrid Meta Heuristic Algorithm

Design Of A Framework For Optimizing Bandwidth Allocation Of...

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IEEE International conference on Emerging & Sustainable Technologies for Power & ICT in a Developing Society (NIGERCON)

作者： Oluwole Akinyokun Abejide Adegoke Bidemi Ashade Joy Achas Olagunju Anuoluwapo Temitope Ogunbiyi Department of Software Engineering Federal University of Technology Akure Ondo State Nigeria Department of Computer Science and Information Technology Bells University of Technology Ota Ogun State Nigeria

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

Video transmission in wireless network poses several challenges such as latency, delayed throughput, slow convergence rate, high error rates, packet losses and many others which make it impossible for users to enjoy Quality of Service (QoS). Video in wireless network presents additional challenges due to unavailability of needed bandwidth. Bandwidth in any organization is a limited resource that is being competed for by the different users. Efficient and effective bandwidth allocation is a vital role in satisfying the QoS requirements for multimedia applications such as video streaming. this research work examined conventional and current techniques for bandwidth optimization. For better bandwidth use, conventional bandwidth allocation techniques are gradually being replaced with optimization algorithms using Genetic Algorithm (GA), Bat Algorithm (BA), Whale Optimization Algorithm (WOA), Tabu Search (TS), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and so on. this work specifically addressed bandwidth challenges using hybrid algorithms of PSO+TS algorithms in optimizing the bandwidth allocation of Bells University of Technology, Ota, Ogun State, Nigeria. the PSO algorithm explores bandwidth by giving high priority to video traffic and low priority to other types of traffic (data traffic) while the TS algorithm exploits the bandwidth. the results were evaluated using CPU time and Worst Case Time complexity of the algorithms. Results showed that with the proposed system, PSO+TS algorithm outperformed other individual algorithms of PSO and TS. Video traffics depending on resolution had higher priority levels and were assigned higher bandwidth while data traffic were assigned low bandwidth and as such video users will be able to stream conveniently with good QoS.

关键词： Wireless networks Heuristic algorithms Metaheuristics Bandwidth Quality of service Streaming media Channel allocation Whale optimization algorithms Time complexity Genetic algorithms

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AI-Optimized Genetic Algorithm for Enhancing Resource Recovery in the Circular Economy

AI-Optimized Genetic Algorithm for Enhancing Resource Recove...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),conference on

作者： Abderrahman Mansouri Bellat Abdelouahad Idriss Bennis Ali Siadat Fatiha Akef Modeling and Simulation of Intelligent Industrial Systems Laboratory (M2S2I) ENSET Mohammedia Hassan II University Casablanca Morocco Laboratory of Design Manufacturing and Control Arts et Metiers ParisTech Metz France Laboratory of Mechanical and Thermal Processes and Control (PCMT) ENSAM Rabat Mohammed V University in Rabat Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

this paper presents a Genetic Algorithm (GA)- based optimization approach aimed at improving circular economy strategies by optimizing recyclability and economic value, while minimizing disassembly complexity and environmental impact. A multi-objective function is established, incorporating essential parameters such recyclability rate, component reuse value, disassembly expenses, carbon footprint, and waste minimization. the GA investigates an optimal balance between sustainability and economic viability using an evolutionary search method that identifies and enhances solutions throughout several generations. the dataset comprises 50 components of end-of-life products, categorized as metals (40%), plastics (30%), and electronic materials (30%), exhibiting recyclability rates between 35% and 95%. the results indicate that the GA attains a 25% enhancement in recyclability, a 30% reduction in disassembly complexity, and a 20% decrease in carbon footprint relative to traditional approaches. the suggested method offers a versatile and scalable decision-making instrument for manufacturers, recyclers, and policymakers, enhancing a more sustainable resource recovery system.

关键词： Systematics Instruments Computational modeling Search methods Decision making complexity theory Sustainable development Optimization Carbon footprint Genetic algorithms

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

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

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Emerging Trends in Electrical, Electronic and Communications Engineering (ELECOM), 2020 3rd International conference on

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

ISBN: (数字)9798331532475

ISBN: (纸本)9798331532482

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 E b /N 0 gains in all tested scenarios, with the maximum achievable E b /N 0 gain being 1 dB when using the 8T2R MIMO configuration in the low BER range.

关键词： 5G mobile communication Forward error correction Market research Parity check codes Mathematical models Polynomials MIMO Gain Wireless fidelity MIMO communication

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Robust Principal Component Analysis Based on Globally-convergent Iteratively Reweighted Least Squares 5

Robust Principal Component Analysis Based on Globally-conver...

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5th International conference on Artificial Intelligence and Pattern Recognition, AIPR 2022

作者： Li, Weihao Fan, Jiulun Zhi, Xiaobin Luo, Xurui Xi'an University of Posts and Telecommunications Xi'an710121 China

ISBN: (纸本)9781450396899

Classical Robust Principal Component Analysis (RPCA) uses the singular value threshold operator (SVT) to solve for the convex approximation of the nuclear norm with respect to the rank of a matrix. However, when the matrix size is large, the SVT operator has a slow convergent speed and high computational complexity. To solve the above problems, in this paper, we propose a Robust principal component analysis algorithm based on Global-convergent Iteratively Reweighted Least Squares (RPCA/GIRLS). In the first stage, the low-rank matrix in the original RPCA model is decomposed into two column-sparse matrix factor products, and the two matrix factors are solved via alternating iteratively reweighted least squares algorithms (AIRLS), thus reducing the computational complexity. However, since the AIRLS is sensitive to the initialization, the updated matrix factor in the first stage is used as the new input data matrix in the second stage, and the matrix factor is updated by the gradient descent step, and finally the optimal low-rank matrix that satisfies the global convergent conditions is obtained. We have conducted extensive experiments on six public video data sets, by comparing the background separation effects of these six videos and calculating their quantitative evaluation indexes, the effectiveness and superiority of the proposed algorithm are verified from both subjective and objective perspectives. © 2022 ACM.

关键词： Computational complexity

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