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arXiv 2023年

作者： Gong, Xian McFarland, Claire McCarthy, Paul Griffith, Colin Rizoiu, Marian-Andrei Faculty of Engineering and Information Technology University of Technology SydneyNSW Australia Beesness Pty Ltd Australia The Data Science Institute University of Technology SydneyNSW Australia School of Computer Science and Engineering UNSW Sydney NSW Australia Australia

Understanding the relationship between emerging technology and research and development has long been of interest to companies, policy makers and researchers. In this paper new sources of data and tools are combined with a novel technique to construct a model linking a defined set of emerging technologies with the global leading R&D spending companies. The result is a new map of this landscape. This map reveals the proximity of technologies and companies in the knowledge embedded in their corresponding Wikipedia profiles, enabling analysis of the closest associations between the companies and emerging technologies. A significant positive correlation for a related set of patent data validates the approach. Finally, a set of Circular Economy Emerging Technologies are matched to their closest leading R&D spending company, prompting future research ideas in broader or narrower application of the model to specific technology themes, company competitor landscapes and national interest concerns. © 2023, CC BY-NC-SA.

关键词： Patents and inventions

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Integrating NLP and Ontology Matching into a Unified System for Automated information Extraction from Geological Hazard Reports

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Journal of Earth Science 2023年第5期34卷 1433-1446页

作者： Qinjun Qiu Zhen Huang Dexin Xu Kai Ma Liufeng Tao Run Wang Jianguo Chen Zhong Xie Yongsheng Pan Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518034China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China Beijing Key Laboratory of Urban Spatial Information Engineering Beijing 100045China School of Geography and Information Engineering China University of GeosciencesWuhan 430074China Wuhan Geomatics Institute Wuhan 430074China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China Geological Environmental Center of Hubei Province Wuhan 430034China Faculty of Earth Resources China University of GeosciencesWuhan 430074China State Key Laboratory of Geological Processes and Mineral Resources China University of GeosciencesWuhan 430078China Wuhan Zondy Cyber Science&Technology Co. Ltd.Wuhan 430074China

Many detailed data on past geological hazard events are buried in geological hazard reports and have not been fully utilized. The growing developments in geographic information retrieval and temporal information retrieval offer opportunities to analyse this wealth of data to mine the spatiotemporal evolution of geological disaster occurrence and enhance risk decision making. This study presents a combined NLP and ontology matching information extraction framework for automatically recognizing semantic and spatiotemporal information from geological hazard reports. This framework mainly extracts unstructured information from geological disaster reports through named entity recognition, ontology matching and gazetteer matching to identify and annotate elements, thus enabling users to quickly obtain key information and understand the general content of disaster reports. In addition, we present the final results obtained from the experiments through a reasonable visualization and analyse the visual results. The extraction and retrieval of semantic information related to the dynamics of geohazard events are performed from both natural and human perspectives to provide information on the progress of events.

关键词： geological hazard report spatiotemporal information geological hazard ontology natural language processing gazetteers onlology machine learning

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A Triple-mode Wideband Filtering Antenna with Planar Configuration by Combining One SIW cavity and Two Half-mode Patch Resonators

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IEEE Antennas and Wireless Propagation Letters 2025年

作者： Liu, Qianwen Li, Chengyu Zhu, Lei Tang, Yiming Lu, Wen-Jun Lyu, Yun-Peng Huang, Feng Nanjing University of Posts and Telecommunications College of Telecommunications and Information Engineering Nanjing210003 China State Key Laboratory of Millimeter Waves Nanjing210003 China Nanjing University of Posts and Telecommunications College of Electronic and Optical Engineering Nanjing210023 China University of Macau Department of Electrical and Computer Engineering Faculty of Science and Technology China

In this letter, a triple-mode wideband filtering antenna with planar configuration is presented. The designed antenna has a single substrate layer, which consists of one half-mode circular patch resonator, one half-mode rectangular patch resonator, and one rectangular SIW cavity, and it is fed through the conventional coaxial probe. On the basis of the field analysis, these three types of resonators are compactly integrated without disturbing the resonant properties of their dominant modes. Given this, three resonant modes of half-TM11, half-TM10, and TE11 are well generated, so as to form a widened operating band. Meanwhile, four radiation nulls are produced from far-field radiation cancellation with the increased radiation boundaries. For validation, a prototype antenna with the center frequency of 2.8 GHz is designed and fabricated. The measured results indicate that the proposed antenna achieves an improved fractional bandwidth of 15.7% under three in-band resonances. Besides, four radiation nulls created at 2.32, 3.22, 3.49, and 3.89 GHz in stopband effectively enhance the out-of-band suppression level. Moreover, low profile of 0.037λ0 is also implemented. © 2002-2011 IEEE.

关键词： Microstrip antennas

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An Efficient Classifier: Kernel SVM-LDA

An Efficient Classifier: Kernel SVM-LDA

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Electrical, Energy, and Artificial Intelligence (EICEEAI), International engineering Conference on

作者： Fahimeh Jamshidian Tehrani Behrooz Nasihatkon Khaled Al-Qawasmi Mohammad Rasmi Al-Mousa Reza Boostani School of Computer Engineering Khajeh Nasir University of Technology Tehran Iran Department of Cyber Security Faculty of Information Technology Zarqa University Zarqa Jordan Faculty of Electrical and Computer Engineering Shiraz University Shiraz Iran

This study aims at designing an efficient combinatorial classifier, which fuses linear discriminant analysis (LDA) and kernel support vector machine (SVM) classifiers. The proposed method is called kernel SVM-LDA which benefits from global property of LDA, simultaneous with localized capability of SVM along with mapping ability of RBF kernel to project input data into a more separable high dimensional space. To assess the proposed scheme, Kernel SVM-LDA was applied to some standard datasets derived from UCI database and then compared to standard LDA and kernel SVM classifiers. Kernel SVM-LDA was also employed in cue-based brain computer interface to classify the left and right imagery movements. The results indicate that the introduced method is more superior to that of LDA and kernel SVM because it surpasses the counterparts in terms of robustness, complexity and performance.

关键词： Support vector machines Fuses Databases Scattering Robustness Linear discriminant analysis Data mining

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5G Channel Estimation Based on Whale Optimization Algorithm

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Wireless Communications and Mobile Computing 2023年第1期2023卷

作者： Nguyen T. H, Phuoc To, Thanh-Nha Tran-Thi, Dung Le-Trung, Quan Faculty of Computer Networks and Communications University of Information Technology Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam Faculty of Electrical and Electronics Engineering University of Technology Ho Chi Minh City Viet Nam

This paper presents a novel approach, based on the whale optimization algorithm (WOA), for channel estimation in wireless communication systems. The proposed method provides a means to accurately estimate the wireless channel, while not requiring the statistical characteristics of the channel. This method uses the WOA to search for the best channel statistical characteristics toward the ultimate goal of having the smallest bit error rate (BER). The proposed approach is aimed at enhancing the efficiency of pilot-based OFDM systems under frequency-selective fading channels used in the performance testing of 5G New Radio gNodeB. In terms of BER and mean square error (MSE), the performance of the proposed WOA-based channel estimation algorithm is evaluated and compared with the conventional least square (LS) and minimum mean square error (MMSE) algorithms. The simulation results demonstrate that the proposed algorithm provides highly competitive performance over the MMSE algorithm and significantly outperforms the LS algorithm in a variety of system configurations. Since the requirement on prior channel statistics information makes the MMSE algorithm impractical or extremely complex, the proposed WOA-based channel estimation algorithm should be a suitable and promising candidate for dealing with channel estimation problems. The simulation framework is implemented in MATLAB and available upon request. © 2023 Phuoc Nguyen T. H. et al.

关键词： Bit error rate

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Authentication mechanisms for IoT system based on distributed MQTT brokers: Review and challenges 18

Authentication mechanisms for IoT system based on distribute...

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18th International Learning and technology Conference, L and T 2021

作者： Kurdi, Hassan Thayananthan, Vijey College of Computer Science and Engineering Taibah University Madinah Saudi Arabia Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia

With the rapid growth of internet connected devices and the tremendous amount of data that could be generated and exchanged in IoT environment, we need to reconsider in the current IoT architecture that based on Cloud computing system, to avoid the issues related to performance and scalability. Message Queue Telemetry Transport (MQTT) is one of promising protocol for data exchange in IoT that could encounter such issues because it relies on central broker located in Cloud, and this may lead to increase network congestion, performance overhead or bottleneck. Therefore, we need to leverage Fog computing by developing a distributed architecture for MQTT that contain multiple brokers. In this case, IoT services can be coordinated and managed between Fog computing and Cloud computing. However, this will open new security challenges for several reasons. Firstly, security procedures need to be modified because MQTT that based on distributed architecture require additional multiple brokers and different communication standards that may increase security threats and increase security management complexity. Secondly, MQTT is inherently lacking efficient security features because it performs username/password-based authentication in a plain text, that protected by cryptographic protocol SSL/TSL which is not consider as lightweight protocol for resources constrained devices. This paper will present taxonomy and realization process of IoT authentication scheme. In addition, the paper will discuss challenges of applying authentication mechanisms for IoT systems that based on distributed MQTT brokers. © 2021 The Authors. Published by Elsevier B.V.

关键词： Internet of things

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Bullyproof Sentinel: Fortifying Online Spaces Against Bullying using Machine Learning

Bullyproof Sentinel: Fortifying Online Spaces Against Bullyi...

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International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Dilshani M.M.T. Vinoshan T. Wijesinghe W.A.S.D. Jathushan V. Amila Senarathne Amali Gunasinghe Faculty of Computing Cyber Security Specialization Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Manager Industry Engagement Unit SLIIT CISCO Academy Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka

In the current social media landscape, cyberbullying and online harassment remain pressing issues. Therefore, we planned a cyberbullying detection system for social media platforms. It can protect online communities from toxic behaviors and make a global impact by fostering a safer and more constructive online environment. We are mainly focused on developing an improved technique to detect bot profiles on social media, developing a mechanism to detect abusive content and sarcasm, developing a mechanism to detect defamatory comments on social media, and developing an effective method for detecting offensive and abusive content in image-format reviews on social media using machine learning algorithms.

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Intrusion Detection System Using a Distributed Ensemble Design Based Convolutional Neural Network in Fog Computing

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Journal of information Hiding and Privacy Protection 2022年第1期4卷 25-39页

作者： Aiming Wu Shanshan Tu Muhammad Wagas Yongjie Yang Yihe Zhang Xuetao Bai Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information TechnologyBeijing University of TechnologyBeijing100124China Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi 23460Pakistan School of Engineering Edith Cowan UniversityJoondalup PerthWA 6027Australia

With the rapid development of the Internet of Things(IoT),all kinds of data are increasing *** storage and computing on cloud servers are increasingly restricted by *** has prompted the development of fog *** computing is to place the calculation and storage of data at the edge of the network,so that the entire Internet of Things system can run more *** main function of fog computing is to reduce the burden of cloud *** placing fog nodes in the IoT network,the data in the IoT devices can be transferred to the fog nodes for storage and *** of the information collected by IoT devices are malicious traffic,which contains a large number of malicious *** IoT devices do not have strong computing power and the ability to detect malicious traffic,we need to deploy a system to detect malicious attacks on the fog *** response to this situation,we propose an intrusion detection system based on distributed ensemble *** system mainly uses Convolutional Neural Network(CNN)as the first-level *** the second level,the random forest will finally classify the prediction results obtained in the first *** paper uses the UNSW-NB15 dataset to evaluate the performance of the *** results show that the model has good detection performance for most attacks.

关键词： Intrusion detection system fog computing convolutional neural network feature selection

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Revisiting Knowledge Transfer for Success Enterprise System Project

Revisiting Knowledge Transfer for Success Enterprise System ...

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2021 International Conference on information technology, ICIT 2021

作者： Hussien, Jamal Abdullateef, Mansoor Kahtan, Hasan Sulaiman, Riza Bangi Malaysia Abdulgabber Abdulhak Consultant Researcher Universiti Malaya Faculty of Computer Science and Information Technology Department of Software Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9781665428705

This paper re-examines the relationship between the Knowledge Transfer (KT) and the project management process groups. Knowledge Transfer as one of the knowledge management life-cycle is supposed to have a remarkable impact on the enterprise system success. However, project failure is one of the main problems in enterprise systems management and lack of proper documentation on the results of previous projects and knowledge transfer are the main reasons. In this paper, we have found that enterprise system project divided into three stages, with (6) process groups in the Pre-Implementation stage, (6) process groups during-Implementation stage, and (3) process groups in the post-Implementation, however, there are eleven (11) roles who are evolving to anticipate the fifth results (Project Proposal, Evaluation Ratings, Project Charter, Project Plan, Project Documents), to increase the understanding of knowledge in each project stages to improve the enterprise system project success. © 2021 IEEE.

关键词： Project management

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A Color-Based Re-Ranking Process for People Re-Identification : Paper ID 21 9

A Color-Based Re-Ranking Process for People Re-Identificatio...

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9th European Workshop on Visual information Processing, EUVIP 2021

作者： Mortezaie, Zahra Hassanpour, Hamid Beghdadi, Azeddine Shahrood University of Technology Faculty of Computer Engineering Shahrood Iran Institut Galilee Universite Paris Laboratory Information Processing and Transmission Cite Villetaneuse France

ISBN: (纸本)9781665432306

People re-identification is a fundamental stage in video surveillance systems. This stage is used for determining the labels of the people's images usually based on their visual similarities. The appearance salience caused by wearing the clothes and carrying objects, with specific colors can be used for improving the performance of re-identification systems. To address the mentioned point, in this paper, we propose a color-based re-ranking process. In the proposed approach first, the input images are semantically segmented as: person's body, possible carried objects, and background. Then the most frequent colors of person's body and possible carried objects are used to re-order the ranked results obtained from two commonly used re-identification approaches i.e., Gaussian of Gaussian (GOG) and Hierarchical Gaussian Descriptors (HGDs). Experimental results on various people re-identification datasets show that our proposed re-ranking approach can improve the performance of re-identification systems. © 2021 IEEE.

关键词： Color

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