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Visual navigation for mobile robots based on deep reinforcement learning

Visual navigation for mobile robots based on deep reinforcem...

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2023 IEEE international conference on Real-Time computing and Robotics, RCAR 2023

作者： Lian, Pengfei Yuan, Liang Sun, Lihui Beijing University of Chemical Technology College of Information Science and Technology Beijing100029 China Beijing University of Chemical Technology Beijing Advanced Innovation Center for Soft Matter Science and Engineering Beijing100029 China Space Engineering University Non Commissioned Officer Academy Beijing102299 China

ISBN: (纸本)9798350327182

Since visual navigation algorithms based on deep reinforcement learning (DRL) suffer from insufficient extraction of spatio-temporal features of images and poor target point-oriented exploration, we propose a new visual navigation framework. The input of the framework consists of three components: the depth images generated by the depth camera at successive moments, the current state of the mobile robot, and the relative position of the target point, which outputs the control commands of the mobile robot in an end-to-end manner through DRL. In addition, we design a feature extractor based on convolutional long short-term memory network (ConvLSTM), which not only captures the correlation between the depth images and target point information at consecutive moments, but also better obtains the key spatial layout and corresponding temporal features from the time-series images, thus reducing the exploration time. The designed network is trained in an unknown simulation environment and random Gaussian noise is added to the depth images to enhance the generalization ability of the network. The results show the algorithm achieves better results in terms of learning rate, convergence and navigation success rate, and also shows good generalization ability across scenes. © 2023 IEEE.

关键词： Reinforcement learning

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Joint Delay and Energy Optimization for WPT-MEC System Based on Immune Algorithm 19th

Joint Delay and Energy Optimization for WPT-MEC System Bas...

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19th EAI international conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2023

作者： Sun, Lu Li, Dianju Lu, Hao Wan, Liangtian Zheng, Jianbo Wang, Xianpeng Department of Communication Engineering Institute of Information Science Technology Dalian Maritime University Dalian116026 China City University of Macau Macau China Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Shenzhen MSU-BIT University Guangdong Shenzhen518172 China School of Software Dalian University of Technology Dalian116620 China Artificial Intelligence Research Institute Shenzhen MSU-BIT University Guangdong Shenzhen518172 China School of Information and Communication Engineering Hainan University Haikou570228 China

ISBN: (纸本)9783031651250

In some production workshops, because the space is too small to be suitable for the layout of the equipment charging device, the joint application of mobile edge computing (MEC) and wireless power transfer (WPT) can solve such problems. However, this scenario has a double near-far effect that is unfair to terminal devices far away from edge servers and energy transfer stations, so this paper considers relay collaboration among devices when computing offloading. This paper uses the frequency division multiple access (FDMA) technology to enable multiple terminals to perform tasks offloading simultaneously. In this paper, the total communication delay and total energy consumption of the system are optimized through effective computing resources scheduling and reasonable tasks allocation, which is a weighting and minimizing problem of normalized system delay and energy consumption rate, and also a NP-hard problem. This paper improves the immune algorithm (IA) in the scenario of multi-server and multi-terminal to obtain the Q-IADE algorithm. The improved Q-IADE algorithm not only has the characteristics of wide application, but also further improves the global search ability, which can better solve the problems we raised. Finally, the simulation results show that the proposed Q-IADE algorithm has strong global search ability and stable convergence effect, and the algorithm performance is superior to the other three comparison algorithms, especially when relay offloading can be performed. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Energy utilization

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Developing a new modified Algorithms for Digital Image Sampling and Quantization in Serial and Parallel Image Processing

Developing a new modified Algorithms for Digital Image Sampl...

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2023 IEEE international conference on Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario, ICPSITIAGS 2023

作者： Jayashankari, J. Shalini, V. Pandey, Megha Swetha, S. Sharma, Mohit Kumar Khurana, Jatin Prince Shri Venkateshwara Padmavathy Engineering College Department of Information Technology Chennai127 India Vishwakarma Institute of Information Technology Department of Information Technology Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology U P India Department of Computer Science and Information Technology Karnataka Bangalore India Vivekananda Global University Department of Electrical Engineering Jaipur India University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350329773

The improvement of a new changed algorithms for virtual photograph sampling and quantization in serial and parallel image processing is proposed. The set of rules improves upon existing methods with the aid of combining picture sampling, quantization, and parallelization techniques with an efficient, in-region serial photograph processing framework. The ensuing algorithm has several advantages, which includes more accurate and steady photograph output, quicker convergence fees, and flexibility in process scheduling. The set of rules is nicely-suitable to parallel computing environments, together with clusters and multi-center structures. Via widespread experimentation and simulation, the proposed set of rules is located to be effective and to outperform present techniques. Moreover, the performance of the proposed set of rules changed into further confirmed thru a comparison to present methods, and the parameters of the version had been tuned in order to optimize overall performance. © 2023 IEEE.

关键词： Image enhancement

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Hybrid Optimization for Scheduling Budget-constrained Energy-aware Workflows in the Cloud

Hybrid Optimization for Scheduling Budget-constrained Energy...

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2023 international conference on Automation in Manufacturing, Transportation and Logistics, iCaMaL 2023

作者： Li, Huifang Du, Mingtong Chen, Boyuan Lu, Xiangyu Chai, Senchun Xia, Yuanqing School of Automation Beijing Institute of Technology Beijing China

ISBN: (纸本)9781839539954

Cloud computing become a popular environment for deploying compute- and data-intensive scientific applications. However, scheduling workflows in cloud datacenters efficiently to meet all parties’ requirements is still a great challenge. This paper proposes a hybrid optimization approach, GBO+GA, which combines the Gradient-Based Optimizer (GBO) and Genetic Algorithm (GA) for scheduling workflows to minimize the makespan under budget and energy consumption constraints. Firstly, an evolution-aware update strategy switching mechanism is designed to use GBO and GA alternatively in the right time and thus to improve the search diversity. Second, a pattern learning-based auxiliary GBO is adopted to update individuals when the whole population gets stuck into local optima, i.e., replacing the best guiding solution in the original GBO with the defined pattern to make the population escape from local optima and explore more potential areas around. Third, to improve the average fitness of the whole population, some bottom ranked individuals are guided by the global best individual to move towards the optimal solution and speed up convergence. Extensive experiments are conducted on four well-known scientific workflows with different scales, and results demonstrate that GB+GA outperforms its peers, GA, GBO and PSO in the success rate, solution quality and convergence. © The Institution of Engineering & technology 2023.

关键词： Budget control

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An EMC Study for Renewable Energy Applications Using AI Algorithms

An EMC Study for Renewable Energy Applications Using AI Algo...

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2023 IEEE international conference on Artificial Intelligence and Green Energy, ICAIGE 2023

作者： Zitouna, Bessem Tlig, Mohamed Hedia, Sassia Hadj Slama, Jaleleddine Ben Université de Sousse Ecole Nationale d'Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia

ISBN: (纸本)9798350325539

In this paper, it has been established that hybrid artificial intelligence (AI) is an efficient tool in performing electromagnetic compatibility (EMC) studies for power electronics systems in renewable energy applications. Indeed, a three-dimensional electromagnetic (EM) inverse method is presented for modeling and characterizing radiating sources using the near-field technique. The proposed method is based on time-domain (TD) analysis. AI-based techniques allow performing sources identification and classification with a guaranteed convergence and an adequate computing time. Indeed, the TD EM inverse method is coupled with a hybrid AI algorithm based on the implementation of a particle swarm optimization (PSO) algorithm along with a Pseudo Zernike Moment Invariant (PZMI) descriptor and an artificial neural network (ANN). The proposed method is applied to a simulation of a structure with a transient radiation behavior, such as those used in renewable energy systems. Configuration parameters are fully mastered to avoid cumulative errors related to experimental measurements. A comparative study has been carried out between reference and estimated EM field distributions using TD inverse method based on the hybrid AI method on the one hand and on genetic algorithms (GA) on the other. Obtained results prove the efficiency of the proposed algorithm, in particular in terms of convergence speed and accuracy. © 2023 IEEE.

关键词： Time domain analysis

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Entanglement Percolation in Noisy Quantum Networks 1

Entanglement Percolation in Noisy Quantum Networks

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1st international conference on Quantum Communications, Networking, and computing, QCNC 2024

作者： Oh, Soo Min Shin, Hyundong Marano, Stefano Conti, Andrea Win, Moe Wireless Information and Network Sciences Laboratory Massachusetts Institute of Technology CambridgeMA United States Kyung Hee University Department of Electronics and Information Convergence Engineering Yongin Korea Republic of University of Salerno Department of Information & Electrical Engineering and Applied Mathematics Fisciano Italy University of Ferrara Department of Engineering and CNIT Ferrara Italy Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA United States

ISBN: (纸本)9798350366778

Quantum networks (QNs) are expected to play a key role in next-generation networks. A QN is comprised of quantum nodes and links (or bonds) representing entangled qubit pairs (EQPs) shared between two nodes. The probability of establishing a pure maximally entangled pair, known as Einstein-Podolsky-Rosen (EPR) pair, between two neighboring nodes represents the linking probability (or bond occupation probability). If such probability exceeds the so-called percolation threshold, the QN exhibits a percolation phenomenon characterized by the emergence of a giant cluster spanning the entire network. In the presence of such a giant cluster, any two arbitrary nodes in the system are connected by a chain of links with a non-zero probability, thus establishing EPR pairs at remote nodes. This work introduces a procedure for obtaining QNs from initially isolated quantum nodes. In the proposed procedure, two copies of EPR pairs are prepared at a source node and two qubits, one from each pair, are sent to a neighboring node through a noisy quantum channel. Then, a pair of mixed quantum states is established between the source node and the neighboring node. By performing local operations and classical communication, an EPR pair can be established between these two nodes with non-zero probability. Repeating this procedure for every pair of source node and neighboring node, a QN exhibiting a percolation phenomenon can be obtained. © 2024 IEEE.

关键词： Quantum channel

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Two-Step Feature Selection Technique for Secure and Lightweight Internet of Things 32

Two-Step Feature Selection Technique for Secure and Lightwei...

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32nd international conference on Computer Communications and Networks, ICCCN 2023

作者： Jeon, So-Eun Oh, Ye-Sol Kil, Ye-Seul Lee, Yeon-Ji Lee, Il-Gu Sungshin Women's University Department of Future Convergence Technology Engineering Seoul02844 Korea Republic of Sungshin Women's University Department of Convergence Security Engineering Seoul02844 Korea Republic of

ISBN: (纸本)9798350336184

With the arrival of the information age, the amount of usable high-dimensional data is rapidly increasing;however, the vast amount of unrefined data may deteriorate the performance of machine learning algorithms. Furthermore, lightweight devices, such as the secure Internet of Things (IoT), have small memory capacity and limited computing power for large data processing;thus, it is difficult to introduce machine learning algorithms to IoT applications. Therefore, it is necessary to develop an efficient learning method that can be used on lightweight devices. This paper proposes a feature selection model consisting of two steps to efficiently reduce the computational complexity of conventional models in the learning process. The proposed two-step feature selection model (TFSM), which performs an exhaustive search for all features by selecting features based on variable importance and then deriving the optimal feature set, significantly reduced complexity, memory usage, and latency with similar accuracy to the greedy model. Particularly, TFSM decreased the complexity by 99.73%, memory usage by 99.97%, and latency by 72.4% compared to the greedy model that uses all features, and improved accuracy by 15.89% compared to random models that randomly perform feature selection. © 2023 IEEE.

关键词： Internet of things

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Analysing How Marketing Management and Artificial Intelligence are used to Change Customer Engagement 2

Analysing How Marketing Management and Artificial Intelligen...

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2nd IEEE international conference on Trends in Quantum computing and Emerging Business Technologies, TQCEBT 2024

作者： Kulkarni, Yogesh Mahamuni, Archana Sane, Sandip Kalshetti, Prashant Patil, Kunal Jarad, Rajendra Subhash Ellicium Solutions India Soil School of Business Design Delhi NCR India Savitribai Phule Pune University ASM's Institute of Business Management and Research Pune India Global Business School and Research Centre Dr. D y Patil Vidyapeeth Department of Bba Pune India Dr D y Patil Institute of Management Studies Akurdi Pune India Dr. D. Y. Patil Institute of Technology Department of Mba Pimpri Pune India

ISBN: (纸本)9798350384277

The integration of marketing management and AI can transform customer engagement strategies across industries. Marketing management underpins business operations, connecting customers and boosting success. AI becomes a key digitization tool as businesses adapt to new technology, processing massive amounts of data and changing customer interactions. This study examines how marketing management and AI interact to change customer engagement dynamics. Marketing management is crucial to business efficiency, customer relations, and growth. Effective marketing strategies help businesses increase revenue, market share, and reputation. Marketing initiatives also support non-profit goals, community engagement, and social causes. Understanding AI tools for customer engagement reveals voice-activated chatbots, sentiment analysis, facial recognition, NLP, and visual search. These AI-powered tools help businesses personalize interactions, interpret customer sentiment, and streamline service delivery, improving customer *** can deliver ultra-personalized solutions, predict consumer preferences, and optimize communication channels using AI tools to improve customer engagement. Companies can boost customer satisfaction, brand loyalty, and market share by using AI-driven insights and analytics. The study explore how AI may affect customer engagement to see its transformative potential across industries. AI helps businesses analyse data, predict consumer behaviour, and personalize interactions, revolutionizing customer experience. However, data privacy, security, and ethics require responsible deployment and strategic adaptation. The convergence of marketing management and AI offers unprecedented opportunities to transform customer engagement strategies. Businesses can improve customer satisfaction, brand loyalty, and digital growth by adopting AI-driven technologies and addressing their challenges. © 2024 IEEE.

关键词： Customer satisfaction

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Behavioral Analysis Using Gamification—A Comprehensive Analysis 11th

Behavioral Analysis Using Gamification—A Comprehensive Anal...

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11th international conference on Intelligent computing and Applications, ICRTC 2023

作者： Garg, Gauri Siddiqui, Hiba Nazim Jain, Naman Tyagi, Shivangi Department of Computer Science and Information Technology KIET Group of Institutions Ghaziabad India

ISBN: (纸本)9789819717231

Gamification is the convergence of game designing and behavioral analysis. The goal of gamification is to increase human motivation and performance with respect to a given pastime. Current software answers promise support for analyzing recreation and gamification-related facts. A recent surge in the popularity of online game-inspired software aimed at addressing difficulties in a range of disciplines, including health care, energy efficiency, learning, and industry, has resulted in a surge in its popularity. These apps are largely centered on the concept of gamification, a term that describes the process of developing non-gaming sports that resemble video games. Gamification has evolved into a fantastic strategy for establishing community connections and fostering social interaction in both current and digital situations. This paper provides a comprehensive overview of how gamification is being used continuously for the analysis of behavioral in people. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Game design

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QIGA: Quantum-Inspired Genetic Algorithm for Dynamic Scheduling in Mobile Edge computing

QIGA: Quantum-Inspired Genetic Algorithm for Dynamic Schedul...

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international CSI Computer conference, CSICC

作者： Sadra Galavani Abolfazl Younesi Mohsen Ansari Department of Computer Engineering Sharif University of Technology Tehran Iran

ISBN: (数字)9798331523114

ISBN: (纸本)9798331523121

This paper introduces a Quantum-Inspired Genetic Algorithm (QIGA) for efficient scheduling in a Mobile Edge computing (MEC) environment. Inspired by the principles of quantum computing, it enhances solution diversity and convergence in the MEC landscape with heterogeneous resources and dynamic tasks. In this work, the QIGA framework is applied to an optimization problem with multiple conflicting objectives: makespan, energy consumption, and resource utilization. Extensive evaluations demonstrate the effectiveness of our proposed method, which shows improvement over three state-of-the-art scheduling methods in varied burst MEC scenarios in energy consumption about 15.7% on average and up to 39%, 20.5% in makespan, 27.5% in resource utilization, and latency up to 69.9%.

关键词： Energy consumption Quantum computing Multi-access edge computing Processor scheduling Dynamic scheduling Resource management Optimization Tuning Genetic algorithms convergence

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