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Emerging Systems and Intelligent Computing (ESIC), International Conference on

作者： Manish Prajapati Santos Kumar Baliarsingh Chinmayee Dora Ashutosh Bhoi Jhalak Hota Jasaswi Prasad Mohanty School of Computer Engineering KIIT Deemed to be University Bhubaneswar India Department of Electronics & Communication Engineering Centurion University of Technology and Management Bhubaneswar India Department of Computer Science & Engineering GITAM Deemed to be University Visakhapatnam India

A large language model (LLM) is a trained deep-learning model that understands and generates text in a human-like fashion. Due to the significant advancements of LLM, it becomes a challenging task to distinguish human-written content from artificial intelligence (AI) generated content. In this work, we leverage the machine learning (ML) models to reliably identify whether an essay is authored by a human being or by an LLM. Concerns about LLMs replacing human tasks, especially in education persist. However, optimism remains for their potential as tools to enhance writing skills. An academic worry is LLMs facilitating plagiarism due to their extensive training in text and code datasets. Using diverse texts and unknown generative models, we replicate typical scenarios to encourage feature learning across models. In a study involving human subjects, we demonstrate that the annotation scheme offered by generative textual likelihood ratio (GLTR) enhances the human detection rate of fake text from 74% to 99% without requiring any previous training. GLTR is open source and publicly deployed, already finding widespread use in detecting generated outputs.

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Hydrate Reformation Characteristics in Offshore Natural Gas Hydrate Reservoir Using the Horizontal Well Depressurization Production

Hydrate Reformation Characteristics in Offshore Natural Gas ...

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Offshore technology Conference, OTC 2025

作者： Zhang, Jianbo Liu, Xiaoao Luo, Jiazheng Sun, Xiaohui Zhong, Jie Wang, Zhiyuan Huang, Weian Sun, Baojiang Wang, Xiao School of Petroleum Engineering China University of Petroleum East China Shandong Qingdao China Shandong Key Laboratory of Offshore Oil & Gas and Hydrates Development Shandong Qingdao China CNPC Engineering Technology R&D Company Limited Beijing China No.7 Oil Production Plant PetroChina Changqing Oilfield Company Shanxi Xian China College of Computer Science and Technology China University of Petroleum East China Qingdao China School of Materials Science and Engineering China University of Petroleum East China Qingdao China

ISBN: (纸本)9781959025610

During depressurization production of natural gas hydrate, the reformation of hydrate is likely to occur in the reservoir, hindering the efficient development of hydrate. Previous studies on the reformation of hydrate in the process of natural gas hydrate production were mainly focused on experimental research and numerical simulation under experimental conditions. In this work, a multi-field coupling flow model considering the effect of hydrate reformation during depressurization production of hydrate reservoir was established, and the accuracy of the model was verified by the field measured data. Meanwhile, the reformation characteristics of hydrate in the reservoir using the horizontal well depressurization production were simulated and investigated. The results show that the reformation of hydrate in the reservoir mainly occurs in the upper part and middle boundary of the hydrate decomposition zone during the depressurization production. Moreover, the smaller the pressure drop extent, absolute permeability and initial hydrate saturation, and the deeper the horizontal well, the larger the hydrate secondary formation zone in the reservoir, the faster the rate of hydrate reformation, and the greater the hydrate saturation caused by hydrate reformation would be, which would make the risk of flow blockage by reformed hydrate in the reservoir rise. The results of this study can provide theoretical support for the safe and efficient development of offshore natural gas hydrate. © 2025, Offshore technology Conference.

关键词： Offshore gas well production

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SSI−FL: Self-sovereign identity based privacy-preserving federated learning

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Journal of Parallel and Distributed Computing 2024年 191卷

作者： Haque, Rakib Ul Touhidul Hasan, A.S.M. Al-Hababi, Mohammed Ali Mohammed Zhang, Yuqing Xu, Dianxiang Department of Electrical & Computer Engineering University of Texas at San Antonio San Antonio United States School of Computer Science & Technology University of Chinese Academy of Sciences Beijing100049 China Division of Computing Analytics and Mathematics School of Science and Engineering University of Missouri-Kansas City Kansas CityMO64110 United States School of Computer Science & Technology University of Chinese Academy of Sciences Beijing101408 China National Computer Network Intrusion Protection Center University of Chinese Academy of Sciences Beijing100049 China

Traditional federated learning (FL) raises security and privacy concerns such as identity fraud, data poisoning attacks, membership inference attacks, and model inversion attacks. In the conventional FL, any entity can falsify its identity and initiate data poisoning attacks. Besides, adversaries (AD) holding the updated global model parameters can retrieve the plain text of the dataset by initiating membership inference attacks and model inversion attacks. To the best of our knowledge, this is the first work to propose a self-sovereign identity (SSI) and differential privacy (DP) based FL namely SSI−FL for addressing all the above issues. The first step in the SSI−FL framework involves establishing a secure connection based on blockchain-based SSI. This secure connection protects against unauthorized access attacks of any AD and ensures the transmitted data's authenticity, integrity, and availability. The second step applies DP to protect against model inversion attacks and membership inference attacks. The third step focuses on establishing FL with a novel hybrid deep learning to achieve better scores than conventional methods. The SSI−FL performance analysis is done based on security, formal, scalability, and score analysis. Moreover, the proposed method outperforms all the state-of-art techniques. © 2024

关键词： Blockchain

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IoT Empowering in Portugal's Agroindustry

IoT Empowering in Portugal's Agroindustry

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Sustainable Computing and Integrated communication in Changing Landscape of AI (ICSCAI), International Conference on

作者： Maitraiyee Konar Manikandan Parasuraman Girija Shankar Sahoo Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India School of Computer Science and Engineering Jain (Deemed to be University) Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (数字)9798350355338

ISBN: (纸本)9798350355345

Natural resources are heavily used by the agro-industrial sector for farming and meat production. By 2050, there will likely be a population rise, which will raise demand and strain already-scarce resources. The Green Deal promise made by the European Commission and the 12th Sustainable Development Goal are both in line with this problem. Agro-food businesses need to increase production and sustainability to overcome this issue. Agro-food enterprises may become more eco-efficient by using the Internet of Things (IoT), especially when it comes to problems like food waste, resource management, and farm production efficiency. Depending on its potential and maturity, IoT implementation varies. A study of 21 micro, mid, and medium-sized agro-food enterprises across sectors was done to assess and categorise businesses in terms of IoT deployment. In addition to offering suggestions for improvement, this article includes information about IoT maturity, complexity, potential, possibilities, solutions, and implementation challenges.

关键词： Training Natural resources Production Information and communication technology Internet of Things Resource management Sustainable development Monitoring Business Strain

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Flexible Localization Method with Motion Estimation for Underwater Wireless Sensor Networks

Flexible Localization Method with Motion Estimation for Unde...

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International Conference on Advanced communication technology (ICACT)

作者： A. S. Ismail Ammar Hawbani Xingfu Wang Samah Abdel Aziz Liang Zhao Nasir Saeed School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China Faculty of Science Zagazig University Zagazig Egypt School of Computer Science Shenyang Aerospace University Shenyang China Department of Electrical and Communication Engineering United Arab Emirates University Al Ain UAE

Due to the challenging conditions of underwater environments, such as node mobility and large-scale networks, achieving localization in large-scale mobile underwater sensor networks (UWSN) is a difficult task. This paper introduces a scheme known as the Flexible Localization Method with Mobility Estimation (FLMME) for UWSNs by utilizing the expected mobility patterns of underwater objects. FLMME performs localization hierarchically by splitting the process into anchor and ordinary node localization. Each node estimates its next mobility pattern based on previous location information, enabling estimates about its next location. Anchor nodes, holding known locations, manage the localization process to balance accuracy and error trade-offs. Extensive simulations demonstrate that FLMME reduces localization errors and hence increases localization accuracy.

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Design of Backward-Pumping RFA Based on Modified Particle Swarm Optimization Algorithm 14

Design of Backward-Pumping RFA Based on Modified Particle Sw...

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14th International Conference on Measuring technology and Mechatronics Automation, ICMTMA 2022

作者： Gong, Jiamin Lu, Jiaojiao Gao, Ruijie Guo, Liufei Wu, Chengchao Pei, Mengjie Liu, Wei School of Electronic Engineering Xi'an University of Posts and Telecommunications Xi'an710121 China School of Communication and Information Engineering Xi'an University of Posts and Telecommunications Xi'an710121 China School of Computer Science and Technology Xi'an University of Posts and Telecommunications Xi'an710121 China

ISBN: (纸本)9781665499781

In order to meet the requirements of the sixth generation mobile communication (6G) system for high speed and large capacity of optical communication network, further improving the bandwidth, response rate and amplification of optical fiber amplifier in optical transmission network has become the focus of current research. Tellurite fiber is used as fiber gain medium, and a modified particle swarm optimization algorithm is proposed, which dynamically adjusts the individual velocity, position and inertial weight values during the iterative process to obtain higher convergence speed and enhance the global search capability. The algorithm is applied to optimize, analyze and verify the configuration of each pump light parameter of Raman fiber amplifier, and finally, the average gain of the backward-pumping Raman fiber amplifier is up to 15.9320dB and the gain fluctuation is about 0.3620dB. The results show that the modified particle swarm optimization algorithm can optimize the Raman fiber amplifier pump power and wavelength accurately and quickly, and can improve the performance of Raman amplifier effectively, which has a certain reference significance for the design of Raman fiber amplifier in the future. © 2022 IEEE

关键词： Fiber amplifiers

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Amplifying Aspect-Sentence Awareness: A Novel Approach for Aspect-Based Sentiment Analysis

SSRN

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SSRN 2024年

作者： Lawan, Adamu Pu, Juhua Haruna, Yunusa Muhammad, Jawad Umar, Aliyu School of Computer Science and Engineering Beihang University Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Jigawa State Institute of Information Technology Kazaure Nigeria

Aspect-Based Sentiment Analysis (ABSA) has gained prominence as a natural language processing (NLP) technique for extracting and analyzing sentiments related to specific aspects or features within text, offering detailed insights from sources like customer reviews and social media feedback. However, existing attention-based models often struggle to effectively connect aspect with context due to language complexity and the presence of multiple sentiment polarities in a single sentence. To address these challenges, we propose Amplifying Aspect-Sentence Awareness (A3SN), a novel technique designed to enhance ABSA by amplifying aspect-sentence awareness. Our approach follows the transformer's standard process and incorporates multi-head attention (MHA) mechanisms to enrich the model with the input text’s semantic information. We introduce an additional enhanced MHA mechanism that amplifies aspect-sentence awareness attention, doubling the attention between the sentence and the aspect to accurately capture subtle relationships and dependencies. Furthermore, a gated fusion mechanism was used to integrates feature representations from the multi-head and amplify aspect-sentence awareness attention modules. Experimental results on three benchmark datasets demonstrate A3SN's effectiveness, outperforming state-of-the-art (SOTA) baseline models, while maintaining simplicity and low computational complexity. © 2024, The Authors. All rights reserved.

关键词： Sentiment analysis

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A behavior-aware SLA-based framework for guaranteeing the security conformance of cloud service

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Frontiers of computer science 2020年第6期14卷 153-169页

作者： Xiaochen LIU Chunhe XIA Tianbo WANG Li ZHONG Xiaojian LI Beijing Key Laboratory of Network Technology School of Computer Science and EngineeringBeihang UniversityBeijing 100191China School of Computer Science and Information Technology Guangxi Normal UniversityGuilin 541004China School of Cyber Science and Technology Beihang UniversityBeijing 100191China

As cloud computing technology turning to mature,cloud services have become a trust-based ***'distrust of the security and performance of cloud services will hinder the rapid deployment and development of cloud *** cloud service providers(CSPs)urgently need a way to prove that the infrastructure and the behavior of cloud services they provided can be *** challenge here is how to construct a novel framework that can effective verify the security conformance of cloud services,which focuses on fine-grained descriptions of cloud service behavior and security service level aggreements(SLAs).In this paper,we propose a novel approach to verify cloud service security conformance,which reduces the description gap between the CSP and users through modeling cloud service behavior and security SLA,these models enable a systematic integration of security constraints and service behavior into cloud while using UPPAAL to check the performance and security *** proposed approach is validated through case study and experiments with real cloud service based on Open-Stack,which illustrates CloudSec approach effectiveness and can be applied on realistic cloud scenario.

关键词： security conformance security SLA cloud be-havior modeling

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Energy-Optimized Offloading of Delay-Sensitive Tasks in Hybrid Edge-Cloud Computing

Energy-Optimized Offloading of Delay-Sensitive Tasks in Hybr...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Haitao Yuan Shen Wang Yaofei Ma Jing Bi Jinhong Yang Jia Zhang MengChu Zhou School of Automation Science and Electrical Engineering Beihang University Beijing China College of Computer Beijing University of Technology Beijing China CSSC Systems Engineering Research Institute Beijing China Dept. of Computer Science Southern Methodist University Dallas TX USA Dept. of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Currently, a cloud-edge collaborative system combines almost unlimited storage and computing resources where tasks can be migrated to high-performance servers in edge servers or the cloud. However, resource allocation and task offloading present big challenges due to the competition among mobile devices (MDs) for communication and computing resources of edge servers. Therefore, it is significant to properly offload MDs' tasks to edge servers or the cloud. This work proposes a collaborative edge-cloud architecture, including a centralized cloud, edge servers, and MDs. Then, this work jointly considers computing power, task sizes, computing resources, transmission power of MDs, transmission rates, computing power, transmission power, computing resource of edge servers, and computing resource of the cloud. Considering the abovementioned factors, this work designs a mixed-integer non-linear programming problem. To solve it, a Genetic Simulated annealing-based Particle Swarm Optimization (GSPSO) algorithm is proposed to obtain the best solution. Building upon it, this work proposes an energy-minimized task offloading and resource allocation strategy, thereby minimizing the system's energy consumption while ensuring strict task response time limits. Experimental results show that GSPSO reduces the system's energy by 66.34%, 34.65%, and 4.95% more than particle swarm optimization (PSO), self-adaptive PSO, and Tyrannosaurus optimization.

关键词： Energy consumption Federated learning Collaboration Simulated annealing Programming Genetics Servers Resource management Particle swarm optimization Optimization

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2-D Wideband DOA Estimation with Circular Arrays Based on the Difference Co-Array Concept

2-D Wideband DOA Estimation with Circular Arrays Based on th...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Hantian Wu Qing Shen Wei Liu Zheng Fu Chenxi Liao School of Information and Electronics Beijing Institute of Technology Beijing China School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Two-dimensional (2-D) direction of arrival (DOA) estimation with a circular array based on the difference co-array has attracted considerable attention in past years. In this paper, the difference co-array position set of a circular array with arbitrary sensor arrangement is derived, and condition under which the maximum number of virtual co-array sensors can be provided by a circular array is presented. Then, an augmented uniform circular array (AUCA) is proposed, providing the maximum number of DOFs for arbitrary number of physical sensors. Compressive sensing based focusing method for the one-dimensional case is extend to 2-D wideband DOA estimation, where focusing on the difference co-array is adopted for performance improvement. Simulations show that better performance can be achieved by our proposed AUCA.

关键词： Direction-of-arrival estimation Circuits and systems Two-dimensional displays Focusing Estimation Integrated circuit modeling Wideband

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