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12TH ANNUAL INTERNATIONAL CONF OF THE SPECIAL INTEREST RESEARCH GROUP ON INFOMATION RETRIEVAL OF THE ASSOC OF COMPUTING MACHINERY

作者： BAEZAYATES, RA GONNET, GH Centre for the New O.E.D. & Data Structuring Group Department of Computer Science University of Waterloo Waterloo Ontario Canada

ISBN: (纸本)0897913213

We introduce a family of simple and fast algorithms for solving the classical string matching problem, string matching with don't care symbols and complement symbols, and multiple patterns. In addition we solve the same problems allowing up to k mismatches. Among the features of these algorithms are that they are real time algorithms, they don't need to buffer the input, and they are suitable to be implemented in hardware.

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A bandwidth adaptation scheme to support QoS requirements of mobile users in wireless environments 9

A bandwidth adaptation scheme to support QoS requirements of...

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9th International Conference on computer Communications and Networks, ICCCN 2000

作者： Aljadhai, AbdulRahman Znati, Taieb F. Computer Technology Department Riyadh College of Technology Riyadh Saudi Arabia Department of Computer Science Telecommunications Program University of Pittsburgh PittsburghPA15260 United States

ISBN: (纸本)0780364945

- This paper presents an adaptive QoS management scheme to accommodate dynamic variations in network resources, due to the mobility of the users and location-dependent errors. The scheme ensures that satisfactory level of QoS guarantees are met regardless of the user mobility. QoS adaptation is achieved based on the use of application specific quality satisfaction curves, while enforcing a fair allocation of bandwidth among the competing flows. The performance of the proposed scheme is evaluated and results indicate that the scheme yields fair adaptation under heavy loads. © 2000 IEEE

关键词： Quality of service

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Assistive IoT-centric Robotics for Senior Living 19

Assistive IoT-centric Robotics for Senior Living

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19th International Conference on Information Technology Based Higher Education and Training, ITHET 2021

作者： Chaczko, Zenon Chiu, Christopher Borowik, Grzegorz Braun, Robin School Of Electrical And Data Engineering University Of Technology Sydney Australia University Of Social Sciences And Humanities Department Of Computer Science Warsaw Poland

ISBN: (纸本)9781728188836

Senior citizens consider the most significant part of aging to be the changes that occur to their bodies. For this reason, they avoid doing body exercises and therefore often prone to heart diseases, muscle disorders and many other ailments. Although weakening of bones and muscles is inevitable as we grow old, we can still maintain our health by doing regular physical exercise. Encouraging elderly people to do physical exercise can be challenging, therefore the Robot-Trainer is introduced to make their exercising journey exciting accompanied by a friendly humanoid robot. The main goal of the system is to program an IoT-Assistive Robot to interact and conduct physical exercise training sessions with elderly people and maintain their physical fitness and mental health. © 2021 IEEE.

关键词： Muscle

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Deep Attention Driven Reinforcement Learning (DAD-RL) for Autonomous Decision-Making in Dynamic Environment

Deep Attention Driven Reinforcement Learning (DAD-RL) for Au...

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

作者： Chowdhury, Jayabrata Shivaraman, Venkataramanan Dangi, Sumit Sundaram, Suresh Sujit, P.B. Indian Institute of Science Robert Bosch Centre for Cyber-Physical Systems Bangalore India Indian Institute of Science Department of Aerospace Engineering Bangalore India Indian Institute of Science Education and Research Department of Data Science & Engineering and Electrical Engineering & Computer Sci-ence Bhopal India

ISBN: (纸本)9781665410205

Autonomous Vehicle (AV) decision-making in ur-ban environments is inherently challenging due to the dynamic interactions with surrounding vehicles. For safe planning, AV/ego must understand the weightage of various spatiotemporal interactions in a scene. Contemporary works use colos-sal transformer architectures to encode interactions mainly for trajectory prediction, resulting in increased computational complexity. To address this issue without compromising spatiotemporal understanding and performance, we propose the simple Deep Attention Driven Reinforcement Learning (DAD-RL) framework, which dynamically assigns and incorporates the significance of surrounding vehicles into the ego's RL-driven decision-making process. We introduce an AV-centric spatiotemporal attention encoding (STAE) mechanism for learning the dynamic interactions with different surrounding vehicles. To understand map and route context, we employ a context encoder to extract features from context maps. The spatiotemporal representations combined with contextual encoding provide a comprehensive state representation. The resulting model is trained using the Soft-Actor Critic (SAC) algorithm. We evaluate the proposed framework on the SMARTS urban benchmarking scenarios without traffic signals to demonstrate that DAD-RL outperforms recent state-of-the-art methods. Furthermore, an ablation study underscores the importance of the context-encoder and spatiotemporal attention encoder in achieving superior performance. © 2024 IEEE.

关键词： Deep reinforcement learning

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Search System for Translation of Al-Qur'an Verses in Indonesian using BM25 and Semantic Query Expansion

Search System for Translation of Al-Qur'an Verses in Indones...

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2021 International Conference on Artificial Intelligence and Big data Analytics, ICAIBDA 2021

作者： Purnama, Arif Rhizky Gilang Yulita, Intan Nurma Helen, Afrida Universitas Padjadjaran Padjadjaran University Research Center for Artificial Intelligence and Big Data Universitas Padjadjaran Department of Computer Science Sumedang Indonesia

ISBN: (纸本)9781665408905

Al-Qur'an is a source of life guidance for Muslims. The digital version of the Qur'an is already available on the android platform. The Indonesian Ministry of Religion provides an official application called the Ministry of Religion's Qur'an which has a translation search system in it. However, adjustments need to be made so that Indonesian people can look for translations of verses that have a definite order based on their level of relevance to the keywords entered. This study aims to develop a search system for translations of Indonesian-language Qur'an verses that already exist in the Ministry of Religion's Qur'an *** study uses the BM25 algorithm with Word2vec as the Semantic Query Expansion method. data as many as 6236 translated documents in the application are used to create a model of the search system. Tests on hyperparameters are carried out to get the most optimal model. The research results obtained several hyperparameter values in SQE including a window of 7, and a query expansion term of 1. In the BM25 hyperparameter, the optimal condition is obtained when the k1 variable is 1.8 and the b variable is 0.85. The search system was evaluated using the Mean Average Precision and compared with the search system that was previously available in the Ministry of Religion's Qur'an. The MAP score increased with the proposed method, from 0.53718 to 0.66556. © 2021 IEEE.

关键词： Semantics

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Maximizing adaptivity in hierarchical topological models using cancellation trees

Maximizing adaptivity in hierarchical topological models usi...

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Workshop on Mathematical Foundations of Scientific Visualization, computer Graphics, and Massive data Exploration, 2004

作者： Bremer, Peer-Timo Pascucci, Valerio Hamann, Bernd Department of Computer Science University of Illinois Urbana-Champaign United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory United States Institute for Data Analysis and Visualization Department of Computer Science University of California Davis United States

ISBN: (纸本)9783642543005

We present a highly adaptive hierarchical representation of the topology of functions defined over two-manifold domains. Guided by the theory of Morse–Smale complexes, we encode dependencies between cancellations of critical points using two independent structures: a traditional mesh hierarchy to store connectivity information and a new structure called cancellation trees to encode the configuration of critical points. Cancellation trees provide a powerful method to increase adaptivity while using a simple, easy-to-implement data structure. The resulting hierarchy is significantly more flexible than the one previously reported (IEEE Trans. Vis. Comput. Graph. 10(4):385–396, 2004). In particular, the resulting hierarchy is guaranteed to be of logarithmic height. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： Trees (mathematics)

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Privacy-aware data Fusion and Prediction for Smart City Services in Edge Computing Environment 15

Privacy-aware Data Fusion and Prediction for Smart City Serv...

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2022 IEEE Congress on Cybermatics: 15th IEEE International Conferences on Internet of Things, iThings 2022, 18th IEEE International Conferences on Green Computing and Communications, GreenCom 2022, 2022 IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2022 and 8th IEEE International Conference on Smart data, Smartdata 2022

作者： Qi, Lianyong Chi, Xiaoxiao Zhou, Xiaokang Liu, Qi Dai, Fei Xu, Xiaolong Zhang, Xuyun School of Computer Science Qufu Normal University China Faculty of Data Science Shiga University Japan Riken Center for Advanced Intelligence Project Japan School of Computer and Software Nanjing University of Information Science and Technology China School of Big Data and Intelligence Engineering Southwest Forestry University China Department of Computing Macquarie University Australia

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

With fast development of Cyber Physical System, the variety and volume of data generated from different edge servers are fairly considerable. Mining and exploiting the data would definitely bring huge advantages. However, there are two major issues exposed in the process. First, utilizing the data with high efficiency is challenging in edge computing environment. Second, data from multiple edge servers often contain sensitive information such as user preferences, which will give rise to privacy breach risks when using the data. Locality-Sensitive Hashing and amplified technology are utilized for dealing with two problems. In this paper, we propose a novel privacy-protection approach named SRchain-LSH in edge computing environment which is based on amplified Locality-Sensitive Hashing technique. In order to verify high accuracy and efficiency of our proposal, large sets of experiments are conducted. According to experimental results, our proposal shows better performance than those of comparative methods in terms of MAE , RMSE and time costs. For our method, the best value of MAE is about 0.41 and time cost is about 0.1 seconds, which are more accurate and efficient than comparative methods. © 2022 IEEE.

关键词： Smart city

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Intrusion Detection in the Internet of Things Using Fusion of GRU-LSTM Deep Learning Model

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Intelligent Automation & Soft Computing 2023年第8期37卷 2279-2290页

作者： Mohammad S.Al-kahtani Zahid Mehmood Tariq Sadad Islam Zada Gauhar Ali Mohammed ElAffendi Department of Computer Engineering Prince Sattam Bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Computer Engineering University of Engineering and TechnologyTaxila47050Pakistan The FAMLIR Group The University of LahoreLahore54000Pakistan Department of Computer Science University of Engineering&TechnologyMardan23200Pakistan Faculty of Computing International Islamic UniversityIslamabad44000Pakistan EIAS Data Science and Blockchain Lab College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia

Cybersecurity threats are increasing rapidly as hackers use advanced *** a result,cybersecurity has now a significant factor in protecting organizational *** detection systems(IDSs)are used in networks to flag serious issues during network management,including identifying malicious traffic,which is a *** remains an open contest over how to learn features in IDS since current approaches use deep learning *** learning,which combines swarm intelligence and evolution,is gaining attention for further improvement against cyber *** this study,we employed a PSO-GA(fusion of particle swarm optimization(PSO)and genetic algorithm(GA))for feature selection on the CICIDS-2017 *** achieve better accuracy,we proposed a hybrid model called LSTM-GRU of deep learning that fused the GRU(gated recurrent unit)and LSTM(long short-term memory).The results show considerable improvement,detecting several network attacks with 98.86%accuracy.A comparative study with other current methods confirms the efficacy of our proposed IDS scheme.

关键词： Cyber security deep learning intrusion detection PSO-GA CICIDS-2017 intelligent system security and privacy IoT

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Driving Behaviour Analysis using Low Sampling GPS Trajectories of Ride-hailing Services 5

Driving Behaviour Analysis using Low Sampling GPS Trajectori...

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5th International Conference on data science and Information Technology, DSIT 2022

作者： Pakeerathan, Thukaraka Santhirakumar, Thenusan Rajendren, Dilani Shegan Perera, Amal Nguyen, Su University of Moratuwa Department of Computer Science & Engineering Moratuwa Sri Lanka Centre for Data Analytics and Cognition La Trobe University Australia

ISBN: (数字)9781665498685

ISBN: (纸本)9781665498685

There is an abundance of existing systems that focus on driver behaviour analysis. The existing driver behaviour analysis is based on average star ratings, driving quality data, customer complaints, and other feedback. It does not provide a view of where a driver's performance is lacking. The dependability of star ratings may vary due to fake ratings, such as self-rating using several devices and passengers being skewed toward excessively poor or high ratings. Also, this is a biased method because there may be no complaints or feedback for particular drivers. Therefore, to identify the deserving drivers, a realistic picture of how the drivers behave on the road while driving can accurately profile driver performance and safety with the collected GPS data for all individual drivers. © 2022 IEEE.

关键词： Quality control

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Statisfy me: What are my stats?

Statisfy me: What are my stats?

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2018 ISWC Posters and Demonstrations, Industry and Blue Sky Ideas Tracks, ISWC-P and D-Industry-BlueSky 2018

作者： Sejdiu, Gezim Ermilov, Ivan Mami, Mohamed Nadjib Lehmann, Jens Smart Data Analytics University of Bonn Germany Department of Computer Science University of Leipzig Leipzig04109 Germany Fraunhofer IAIS Germany

The increasing adoption of the Linked data format, RDF, over the last two decades has brought new opportunities. It has also raised new challenges though, especially when it comes to managing and processing large amounts of RDF data. In particular, assessing the internal structure of a data set is important, since it enables users to understand the data better. One prominent way of assessment is computing statistics about the instances and schema of a data set. However, computing statistics of large RDF data is computationally expensive. To overcome this challenging situation, we previously built DistLODStats, a framework for parallel calculation of 32 statistical criteria over large RDF datasets, based on Apache Spark. Running DistLODStats is, thus, done via submitting jobs to a Spark cluster. Often times, this process is done manually, either by connecting to the cluster machine or via a dedicated resource manager. This approach is inconvenient as it requires acquiring new software skills as well as the direct interaction of users with the cluster. In order to make the use of DistLODStats easier, we propose in this paper an approach for triggering RDF statistics calculation remotely simply using HTTP requests. DistLODStats is built as a plugin into the larger SANSA Framework and makes use of Apache Livy, a novel lightweight solution for interacting with Spark cluster via a REST Interface. © 2018 CEUR-WS. All rights reserved.

关键词： Statistics

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