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19th International Conference on Web information systems and Applications, WISA 2022

作者： Cai, Hanjun Zhao, Feng Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9783031203084

Commonsense knowledge (CSK) is the information that people use in daily life but do not often mention. It summarizes the practical knowledge about how the world works. Existing machines have knowledge but lack commonsense because they do not understand and master commonsense knowledge in the same way that humans do. In the latest works, crowdsourcing-based method is costly and has low coverage, knowledge base completion method can highly fit samples, and methods extracted from unstructured data have the defects of low quality. CG &BF is commonsense knowledge construction with a concept-based generator and a BERT-based filter. We utilize semantic search for node matching and entropy encoder for filtering triples with high abstraction. Two algorithms based on concept aggregation and path credibility are proposed to obtain high-quality CSK triples. We subsequently finetuning a BERT to filter incorrect triples. We obtain 500,000 CSK triples based on ConceptNet, which is superior to other construction methods in novelty and quality. In the reading comprehension task, the three-way attention network is selected as the basic model and the knowledge we generate enables the base model to perform better, which proves that the output of CG &BF has higher quality and ease of use. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Knowledge graph

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Traj-LLM: A New Exploration for Empowering Trajectory Prediction With Pre-Trained Large Language Models

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-14页

作者： Lan, Zhengxing Liu, Lingshan Fan, Bo Lv, Yisheng Ren, Yilong Cui, Zhiyong School of Transportation Science and Engineering Beihang University Beijing China Beijing Key Laboratory of Traffic Engineering College of Metropolitan Transportation Beijing University of Technology Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Transportation Science and Engineering State Key Lab of Intelligent Transportation System Beihang University Beijing China

Predicting the future trajectories of dynamic traffic actors is a cornerstone task in autonomous driving. Though existing notable efforts have resulted in impressive performance improvements, a gap persists in scene cognitive and understanding of complex traffic semantics. This paper proposes Traj-LLM, the first to investigate the potential of using pre-trained Large Language Models (LLMs) without explicit prompt engineering to generate future motions from vehicular past trajectories and traffic scene semantics. Traj-LLM starts with sparse context joint encoding to dissect the agent and scene features into a form that LLMs understand. On this basis, we creatively explore LLMs' strong understanding capability to capture a spectrum of high-level scene knowledge and interactive information. To emulate the human-like lane focus cognitive function and enhance Traj-LLM's scene comprehension, we introduce lane-aware probabilistic learning powered by the Mamba module. Finally, a multi-modal Laplace decoder is designed to achieve scene-compliant predictions. Extensive experiments manifest that Traj-LLM, fueled by prior knowledge and understanding prowess of LLMs, together with lane-aware probability learning, transcends the state-of-the-art methods across most evaluation metrics. Moreover, the few-shot analysis serves to substantiate Traj-LLM's performance, as even with merely 50% of the dataset, it surpasses the majority of benchmarks relying on complete data utilization. This study explores endowing the trajectory prediction task with advanced capabilities inherent in LLMs, furnishing a more universal and adaptable solution for forecasting agent movements in a new way. IEEE

关键词： Semantics

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RGraph: Asynchronous graph processing based on asymmetry of remote direct memory access

RGraph: Asynchronous graph processing based on asymmetry of ...

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作者： Chen, Hanhua Yuan, Jie Jin, Hai Wang, Yonghui Wu, Sijie Jiang, Zhihao National Engineering Research Center for Big Data Technology and System Cluster and Grid Computing Lab Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

The scale of real-world graphs is constantly growing. To deal with large-scale graphs, distributed graph processing has attracted much research efforts. Existing distributed graph processing systems are commonly built on traditional TCP/IP communication stack, which leads to network bottleneck because of low bandwidth and heavy kernel stack operations. Meanwhile, in real power-law graphs, the average number of mirror vertices after graph partitioning is very large, resulting in significant communication overhead among nodes. The emerging high-performance Remote Direct Memory Access (RDMA) network has the features of low latency, high bandwidth, and low CPU overhead, which brings new opportunities for distributed graph processing systems. Existing RDMA-assisted graph processing systems focus on synchronous execution, which imposes barriers between consecutive iterations. Synchronous execution transfers bulk data among nodes and thus only needs a small number of network transfers. However, synchronous execution is usually less efficient than asynchronous execution because of bulk synchronization. Asynchronous execution accelerates graph processing by eliminating barriers, which in turn requires to transfer a large amount of small size data. In this paper, we propose RGraph, an RDMA-assisted asynchronous distributed graph processing system. RGraph distributes edges into two parts to isolate master and mirror vertices. RGraph exploits the asymmetry of RDMA to accelerate the one-to-many communication between master and mirror vertices. We implement RGraph on top of PowerGraph and conduct comprehensive experiments with large-scale real graphs to evaluate its performance. Results show that compared to existing designs, RGraph reduces the execution time by up to 81%. © 2021 John Wiley & Sons Ltd.

关键词： Mirrors

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Optimal Load Forecasting Model for Peer-to-Peer Energy Trading in Smart Grids

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Computers, Materials & Continua 2022年第1期70卷 1053-1067页

作者： Lijo Jacob Varghese K.Dhayalini Suma Sira Jacob Ihsan Ali Abdelzahir Abdelmaboud Taiseer Abdalla Elfadil Eisa Department of Electrical and Electronics Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Electrical and Electronics Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science and Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia Department of Information Systems King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia

Peer-to-Peer(P2P)electricity trading is a significant research area that offers maximum fulfilment for both prosumer and *** also decreases the quantity of line loss incurred in Smart Grid(SG).But,uncertainities in demand and supply of the electricity might lead to instability in P2P market for both prosumer and *** recent times,numerous Machine Learning(ML)-enabled load predictive techniques have been developed,while most of the existing studies did not consider its implicit features,optimal parameter selection,and prediction *** order to overcome fulfill this research gap,the current research paper presents a new Multi-Objective Grasshopper Optimisation Algorithm(MOGOA)with Deep Extreme Learning Machine(DELM)-based short-term load predictive technique i.e.,MOGOA-DELM model for P2P Energy Trading(ET)in *** proposed MOGOA-DELM model involves four distinct stages of operations namely,data cleaning,Feature Selection(FS),prediction,and parameter *** addition,MOGOA-based FS technique is utilized in the selection of optimum subset of ***,DELM-based predictive model is also applied in forecasting the load *** proposed MOGOA model is also applied in FS and the selection of optimalDELM parameters to improve the predictive *** inspect the effectual outcome of the proposed MOGOA-DELM model,a series of simulations was performed using UK Smart Meter *** the experimentation procedure,the proposed model achieved the highest accuracy of 85.80%and the results established the superiority of the proposed model in predicting the testing data.

关键词： Peer to Peer energy trade smart grid load forecasting machine learning feature selection

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Fiber Optic Hydrophone Towed Cable Shape Perception Based on Optical Frequency Domain Reflectometry

Fiber Optic Hydrophone Towed Cable Shape Perception Based on...

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CLEO: Applications and technology in CLEO 2024, CLEO: A and T 2024 - Part of Conference on Lasers and Electro-Optics

作者： Ai, Ke Lv, Yuejuan Chen, Junfeng Fan, Cunzheng Li, Hao Yan, Zhijun Sun, Qizhen School of Optical and Electronics Information Huazhong University of Science and Technology Hubei Wuhan430074 China National Engineering Research Center for Next Generation Internet Access System Hubei Wuhan430074 China

A fiber optic hydrophone towed cable shape perception scheme based on OFDR is proposed and demonstrated. The maximum reconstruction error is 1.25% for the 5 m towed cable with a bending radius of 2.5 m. © Optica ... 详细信息

ISBN: (纸本)9781957171395

关键词： Frequency domain analysis

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Towards Classifying File Segments in Memory Using Machine-Learning 9

Towards Classifying File Segments in Memory Using Machine-Le...

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9th International Conference on information technology Trends, ITT 2023

作者： Al-Saleh, Mohammed I. Alkouz, Akram Alarabeyyat, Abdulsalam Bouchahma, Majed Jordan University of Science and Technology Computer Science Department Jordan Higher Colleges of Technology Computer Information System United Arab Emirates Al-Balqa Applied University Software Engineering Department Jordan-Salt Jordan

ISBN: (纸本)9798350327502

Digital media triage is a main challenge that faces a digital investigator. Knowing what might be useful during crime investigation could greatly save the investigator's time and enhance outcomes. Memory investigation can get potential benefit from the triage process because of its scattered and diverse contents. The Operating system's paging scheme might map the contents of a file into non-consecutive page frames in the physical memory, making the file-type classification and identification process harder. This paper tackles the memory content triage problem at the page level using a machine-learning methodology. © 2023 IEEE.

关键词： Digital storage

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Polyphenol-mediated interfacial deposition strategy for supported manganese oxide catalysts with excellent pollutant degradation performance

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Chinese Chemical Letters 2024年第5期35卷 493-498页

作者： Dong Cheng Youyou Feng Bingxi Feng Ke Wang Guoxin Song Gen Wang Xiaoli Cheng Yonghui Deng Jing Wei The Key Laboratory of Biomedical Information Engineering of Ministry of Education State Key Lab of Transducer TechnologySchool of Life Science and TechnologyXi’an Jiaotong UniversityXi’an 710049China School of Environmental and Municipal Engineering Xi’an University of Architecture and TechnologyXi’an 710055China Department of Chemistry State Key Laboratory of Molecular Engineering of PolymersState Key Laboratory of Transducer TechnologyFudan UniversityShanghai 200433China Key Laboratory of Functional Inorganic Material Chemistry Ministry of EducationSchool of Chemistry and Materials ScienceHeilongjiang UniversityHarbin 150080China

In persulfate-based advanced oxidation process(PS-AOPs),fixing nanosized metal oxide on processable substrates is highly desirable to avoid the aggregation and loss of nanocatalysts during the practical ***,it is still challenging to develop a versatile strategy for the deposition of metal oxide nanocatalysts on various substrates with different physicochemical ***,polyphenols are utilized as a“molecular glue”and reductant to mediate the interfacial deposition of MnO_(2) nanocatalysts on different ***_(2) nanocatalysts were in-situ grown on macroscope mineral substrates(e.g.,airstone)via an interfacial redox strategy between tannic acid(TA)and oxidized KMnO4,and then employed as a fixed catalyst of peroxymonosulfate(PMS)activation for treating pharmaceutical and personal care products(PPCPs)in *** fixed MnO_(2) exhibited superior catalytic performance toward different PPCPS via a singlet oxygen(^(1)O_(2))-dominated nonradical oxidation *** in the secondary effluent of wastewater treatment plants could be effectively removed by a fixed-bed column of the fixed MnO_(2) with long term *** cycle of Mn^(4+)/Mn^(3+)and surface hydroxyl group of the fixed MnO_(2) was proved to be responsible for the activation of *** work provides a new avenue for developing fixed metal oxides for sustainable water treatment.

关键词： Redox strategy Manganese oxides Fixed catalyst Peroxymonosulfate PPCPs

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Channel Fading Emulation for Highly Dynamic Communication Scenarios

Channel Fading Emulation for Highly Dynamic Communication Sc...

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2024 IEEE International Conference on Computational Electromagnetics, ICCEM 2024

作者： Fang, Sheng Yang, Ling Ma, Jian Xie, Yuetian Song, Maozhong Song, Lixin Hua, Boyu Zhu, Qiuming Shi, Dan College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Aviation Key Laboratory of Science and Technology On Aero Electromechanical System Integration Nanjing211106 China Electronic Science and Technology Beijing University of Posts & Telecommunications Beijing100876 China

ISBN: (纸本)9798350383317

Highly dynamic communication terminals have a crucial role in future communication networks. In this article, a channel emulator is designed and implemented on a Field Programmable Gate Array (FPGA) platform to generate channel fading for highly dynamic communication. To reproduce the fast time-varying channel characteristics, a hardware time-evolution method of channel parameters based on scenario-dependent information is proposed. The measurement results indicate that the proposed channel emulator achieves continuity in the time evolution of channel parameters, and the Doppler power spectral density of the emulated channel match the theoretical results, validating the effectiveness of the emulator. © 2024 IEEE.

关键词： Fading channels

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A method of relay UAV deployment for emergency communication scenarios in disaster areas

A method of relay UAV deployment for emergency communication...

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2024 China Automation Congress, CAC 2024

作者： Tao, Cancan Liu, Bowen Han, Yi Chen, Qiangqiang Ye, Jun Zhong, Ronglin School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Parallel Robot and Mechatronic System Laboratory of Hebei Province Yanshan University Qinhuangdao066004 China Faculty of Science Kunming University of Science and Technology Kunming650500 China School of Biological Science and Medical Engineering Beihang University Beijing100191 China School of Information Science and Technology University of Science and Technology of China Hefei230026 China

ISBN: (纸本)9798350368604

This article proposes a relay deployment method that uses UAVs to provide communication services to ground users, especially for emergency communication scenarios in disaster ***, a two-layer network communication model is constructed for emergency communication scenarios in disaster areas, and the relay deployment problem is transformed into a multi-objective optimization problem. On this basis, a detailed analysis of the problem is conducted, and a UAV relay deployment method based on the K-means++ algorithm is proposed. The two indicators of the number of UAVs used and the network communication performance are considered in solving the problem. Simulation results show that the proposed method can achieve a balance between the number of relay UAVs used and the achieved network performance. © 2024 IEEE.

关键词： Multiobjective optimization

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Wearable Microfiber-Based Senor Chip with Active Adaptive Pressure Unit for Cardiovascular Assessment

Wearable Microfiber-Based Senor Chip with Active Adaptive Pr...

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CLEO: Applications and technology in CLEO 2024, CLEO: A and T 2024 - Part of Conference on Lasers and Electro-Optics

作者： Liu, Yunfei Li, Liangye Cai, Heyi Sheng, Shunfeng Xu, Wangyang Shi, Zhengxuan Yan, Zhijun Sun, Qizhen School of Optical and Electronic Information Huazhong University of Science and Technology Hubei Wuhan430074 China National Engineering Research Center for Next Generation Internet Access System Hubei Wuhan430074 China

We presented an accurate and wearable microfiber-based sensor chip with an active pressure adaptation unit for cardiovascular assessment, exhibiting an accuracy of 93.75% for arteriosclerosis assessment and errors of ... 详细信息

关键词： Microfibers

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