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arXiv 2024年

作者： Ramadan, Qusai Boukhers, Zeyd AlShaikh, Muath Lange, Christoph Jürjens, Jan Institute of Software Engineering University of Koblenz Germany Fraunhofer Institute for Applied Information Technology FIT Uniklinik Köln Germany College of Computing and Informatics Saudi Electronic University Saudi Arabia Fraunhofer Institute for Applied Information Technology FIT RWTH Aachen University Germany University of Koblenz Fraunhofer-Institute for Software and Systems Engineering ISST Germany

Traditional data monetization approaches face challenges related to data protection and logistics. In response, digital data marketplaces have emerged as intermediaries simplifying data transactions. Despite the growing establishment and acceptance of digital data marketplaces, significant challenges hinder efficient data trading. As a result, few companies can derive tangible value from their data, leading to missed opportunities in understanding customers, pricing decisions, and fraud prevention. In this paper, we explore both technical and organizational challenges affecting data monetization. Moreover, we identify areas in need of further research, aiming to expand the boundaries of current knowledge by emphasizing where research is currently limited or lacking. © 2024, CC BY.

关键词： Commerce

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FT-AED: benchmark dataset for early freeway traffic anomalous event detection 24

FT-AED: benchmark dataset for early freeway traffic anomalou...

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Proceedings of the 38th International Conference on Neural Information Processing systems

作者： Austin Coursey Junyi Ji Marcos Quinones-Grueiro William Barbour Yuhang Zhang Tyler Derr Gautam Biswas Daniel B. Work Institute for Software Integrated Systems and Department of Computer Science Vanderbilt University Institute for Software Integrated Systems and Department of Civil and Environmental Engineering Vanderbilt University Institute for Software Integrated Systems Department of Computer Science Vanderbilt University Institute for Software Integrated Systems and Department of Computer Science and Department of Civil and Environmental Engineering Vanderbilt University

ISBN: (纸本)9798331314385

Early and accurate detection of anomalous events on the freeway, such as accidents, can improve emergency response and clearance. However, existing delays and mistakes from manual crash reporting records make it a difficult problem to solve. Current large-scale freeway traffic datasets are not designed for anomaly detection and ignore these challenges. In this paper, we introduce the first large-scale lane-level freeway traffic dataset for anomaly detection. Our dataset consists of a month of weekday radar detection sensor data collected in 4 lanes along an 18-mile stretch of Interstate 24 heading toward Nashville, TN, comprising over 3.7 million sensor measurements. We also collect official crash reports from the Tennessee Department of Transportation Traffic Management Center and manually label all other potential anomalies in the dataset. To show the potential for our dataset to be used in future machine learning and traffic research, we benchmark numerous deep learning anomaly detection models on our dataset. We find that unsupervised graph neural network autoencoders are a promising solution for this problem and that ignoring spatial relationships leads to decreased performance. We demonstrate that our methods can reduce reporting delays by over 10 minutes on average while detecting 75% of crashes. Our dataset and all preprocessing code needed to get started are publicly released at https://***/ft-aed/ to facilitate future research.

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Enhanced Butterfly Optimization Algorithm for Large-Scale Optimization Problems

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Journal of Bionic engineering 2022年第2期19卷 554-570页

作者： Yu Li Xiaomei Yu Jingsen Liu Institute of Management Science and Engineering and School of BusinessHenan UniversityKaifeng 475004China School of Business Henan UniversityKaifeng 475004China Institute of Intelligent Network Systems and Software SchoolHenan UniversityKaifeng 475004China

To solve large-scale optimization problems,Fragrance coefficient and variant Particle Swarm local search Butterfly Optimization Algorithm(FPSBOA)is *** the position update stage of Butterfly Optimization Algorithm(BOA),the fragrance coefficient is designed to balance the exploration and exploitation of *** variant particle swarm local search strategy is proposed to improve the local search ability of the current optimal butterfly and prevent the algorithm from falling into local optimality.192000-dimensional functions and 201000-dimensional CEC 2010 large-scale functions are used to verify FPSBOA for complex large-scale optimization *** experimental results are statistically analyzed by Friedman test and Wilcoxon rank-sum *** attained results demonstrated that FPSBOA can better solve more challenging scientific and industrial real-world problems with thousands of ***,four mechanical engineering problems and one ten-dimensional process synthesis and design problem are applied to FPSBOA,which shows FPSBOA has the feasibility and effectiveness in real-world application problems.

关键词： Butterfy optimization algorithm Fragrance coefcient Variant particle swarm local search Large-scale optimization problems Real-world application problems

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Opinion Formation and Social Impact in Networks with Natural and Artificial Intelligence systems 16

Opinion Formation and Social Impact in Networks with Natural...

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16th International Conference Management of Large-Scale System Development, MLSD 2023

作者： Tsarev, Dmitriy Avdyushina, Anna Alodjants, Alexander Itmo University Institute of Advanced Data Transfer Systems St. Petersburg Russia Itmo University Faculty of Software Engineering and Computer Systems St. Petersburg Russia

ISBN: (纸本)9798350337907

We suggest a new quantum-like approach to study distributed intelligence systems (DIS) consisting of natural (owners) and artificial (avatars) intelligence agents organized in a scale-free network. We demonstrate the complex features of social impact in DIS that imply the hierarchical formation of opinion leaders in the network and their topological protection. We elucidated the effect of significant narrowing of the spread of opinions within the network when most owners chose their position as limiting (extreme). © 2023 IEEE.

关键词： Multi agent systems

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Adaptive-extremum seeking control algorithm to seek the odor source using a multi-agent system 41

Adaptive-extremum seeking control algorithm to seek the odor...

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第41届中国控制会议

作者： Meh Jabeen Qing-Hao Meng Li-Cheng Jin Sheng Jin Zhen-Yu Deng Institute of Robotics and Autonomous Systems School of Electrical and Information EngineeringTianjin University Department of Software Engineering The University of Lahore Tianjin Fire Science and Technology Research Institute of MEM

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This study aims to seek the odor source using a multi-agent *** main challenge of the odor source seeking is to search the optimal extremum in the presence of multiple local extrema in a gradient complex *** this,an adaptive-extremum seeking control(adaptive-ESC) algorithm has been *** are navigated to the vicinity of the source based on an estimated gradient using *** the proposed algorithm,both the integral gain and the amplitude of the perturbation signal are adjusted *** local convergence of the algorithm has been proved using averaging *** performance of the proposed algorithm is validated through simulations by employing a multi-agent system.

关键词： Odor source seeking Extremum seeking control Adaption approaches

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A survey for light field super-resolution

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High-Confidence Computing 2024年第1期4卷 118-129页

作者： Mingyuan Zhao Hao Sheng Da Yang Sizhe Wang Ruixuan Cong Zhenglong Cui Rongshan Chen Tun Wang Shuai Wang Yang Huang Jiahao Shen State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Key Laboratory of Data Science and Intelligent Computing International Innovation InstituteBeihang UniversityHangzhou 311115China State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Compared to 2D imaging data,the 4D light field(LF)data retains richer scene’s structure information,which can significantly improve the computer’s perception capability,including depth estimation,semantic segmentation,and LF ***,there is a contradiction between spatial and angular resolution during the LF image acquisition *** overcome the above problem,researchers have gradually focused on the light field super-resolution(LFSR).In the traditional solutions,researchers achieved the LFSR based on various optimization frameworks,such as Bayesian and Gaussian *** learning-based methods are more popular than conventional methods because they have better performance and more robust generalization *** this paper,the present approach can mainly divided into conventional methods and deep learning-based *** discuss these two branches in light field spatial super-resolution(LFSSR),light field angular super-resolution(LFASR),and light field spatial and angular super-resolution(LFSASR),***,this paper also introduces the primary public datasets and analyzes the performance of the prevalent approaches on these ***,we discuss the potential innovations of the LFSR to propose the progress of our research field.

关键词： Light field super-resolution Convolutional neural network Transformer Sub-aperture image Epipolar-plane image

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GenreNet: A Deep Based Approach for Music Genre Classification

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SN Computer Science 2024年第8期5卷 1-10页

作者： Bala Ganesh, N. Bhuvaneswari, M.S. Bhagavathi Sankar, K. Ganesh, P. Department of Software and Systems Engineering Vellore Institute of Technology Tamilnadu Vellore India Department of Smart Computing Vellore Institute of Technology Tamilnadu Vellore India Ciena India Haryana Gurgaon India Tata Consultancy Services Tamilnadu Chennai India

Neural network-based Music Genre Classification is a key component in helping users narrow down the selection of songs and listen to music in a certain genre. Audio segmentation has been done as a preprocessing step on the available audio files using the benchmark dataset “GTZAN”. To improve accuracy, audio segmentation divides a 30-s audio recording into ten 3-s audio files. Segments are utilized to create spectrograms, which are then used to extract features. A spectrogram is a visual depiction of a signal’s frequency band. Applying techniques like magphase and Short Time Fourier Transform to the audio data enhances the quality of the spectrograms. Adaptive Moment estimation, Nesterov-accelerated Adaptive Moment estimation (NADAM), Adaptive Moment estimation with Maximum, and Root Mean Squared Propagation are among the optimization techniques used for feature weight optimization to increase the classification rate. NADAM is found to be effective based on performance measures. The proposed GenreNet model is compared with the state-of-art techniques and performance measures such as Accuracy, Precision, Recall, Root Mean Square Error, F1 Score, Loss and Sensitivity have yielded positive results. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Alexnet18 Audio classification CNN MGC Music genre classification Spectrogram SVM

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Computer-Vision-Based Non-Contact Paste Concentration Measurement*

Computer-Vision-Based Non-Contact Paste Concentration Measur...

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2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024

作者： Liang, Tailin Yuan, Zhaolin School of Computer Science and Engineering Beihang University State Key Laboratory of Software Development Environment Beijing China Research Institute of Advanced Manufacturing Hong Kong Polytechnic University Department of Industrial and Systems Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350378658

For monitoring the paste concentration, existing techniques, such as ultrasonic concentration meters and neutron meters, suffer from radiation hazards and low precision in high concentrations. This paper proposes a novel non-contact concentration measurement method based on deep learning. With the dataset collected by preparing the paste with different concentrations and taking photographs from the paste surface, a convolutional neural network is trained to extract the features from images and predict the concentration. The experiments indicate that the measurement accuracy is close to 88.79 % for the manual stirring paste dataset and 91.42 % for the automatic stirring paste dataset, which are sufficient in industrial applications. As a substitution of traditional concentration measurement instruments, the proposed vision-based concentration measurement method is non-contact and its accuracy is sufficient in industrial applications. © 2024 IEEE.

关键词： Radiation hazards

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Brick by Brick - Findings of an of-the-Shelf Automation System Application for Building Block Component Group Disassembly

Brick by Brick - Findings of an of-the-Shelf Automation Syst...

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Mechanical engineering and Robotics Research (ICMERR), International Conference on

作者： Dominique Briechle Tobias Geger Lena Schartow Andreas Rausch Institute for Software and Systems Engineering Clausthal University of Technology Clausthal-Zellerfeld Germany

ISBN: (数字)9798331509262

ISBN: (纸本)9798331509279

Automation is one of the key drivers in today's global economy. It ensures the conduction of a manifold of standardized processes which helps tackle the decreasing amount of skilled workers in certain areas as well as reducing cost. Although automation is broadly used nowadays, the overall applicability of automated processes is often limited to use cases with predefined process steps of minor flexibility. However, new and upcoming sustainable industries that are focusing on product life-cycle prolonging (e.g. repair, refurbish, and remanufacture (3Rs)) options to enable Circular Economy-friendly treatment, require a high amount of adaptability in automated systems to tackle the high variability of product compositions in disassembly scenarios. The goal of the conducted case study is therefore to investigate the possibilities of a nowadays available of-the-shelf automation system regarding its functions and mechanisms towards enabling automated adaptability by using disassembly scenarios of component groups consisting of different building blocks as an example scenario and the concluding future research areas. The paper, therefore, investigates the different methods offered by the default system and applies them to various levels of disassembly scenarios. The conducted study helps to clarify the capabilities of the system's functionalities in the overall goal to enhance adaptability in disassembly processes.

关键词： Manifolds Industries Computer vision Automation Costs Focusing Collaborative robots Maintenance engineering Mechanical engineering

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Analysis of Bitcoin Fork by Colored Petri Nets

Analysis of Bitcoin Fork by Colored Petri Nets

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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Zhou, Zeyu Liu, Ding Shmeleva, Tatiana R. Zaitsev, Dmitry A. School of Mechano-Electronic Engineering Xidian University Xi'an710071 China Max Planck Institute for Software Systems Saarbruecken Kaiserslautern Germany School of Computing University of Derby United Kingdom

ISBN: (纸本)9781665410205

Bitcoin is under the threat of fork since it operates with a distributed ledger. Predicting the fork probability in advance is beneficial for taking early action to avoid malicious attacks. In this study, we compose a colored Petri net model of Bitcoin. Our model consists of a given number of nodes, and each node has five subpages representing the node structure: proof of work, broadcast blocks, verify blocks, and the process of adding blocks to blockchain, respectively. Simulation results of fork probability can be easily obtained and analyzed by observing the data in the measuring components of subpages. The results show that our model correctly simulates the fork probability: on recent Bitcoin data, compared with the results of the wide-known SimBlock simulator, a difference of some 4.3% has been obtained. Thus, taking into account vivid graphical representation, our model has certain advantages for the developing techniques of attack avoidance. © 2024 IEEE.

关键词： Petri nets

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