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Author Correction: Spatial communication systems across languages reflect universal action constraints

Nature human behaviour 2024年第1期8卷 181页

作者： Kenny R Coventry Harmen B Gudde Holger Diessel Jacqueline Collier Pedro Guijarro-Fuentes Mila Vulchanova Valentin Vulchanov Emanuela Todisco Maria Reile Merlijn Breunesse Helen Plado Juergen Bohnemeyer Raed Bsili Michela Caldano Rositsa Dekova Katharine Donelson Diana Forker Yesol Park Lekhnath Sharma Pathak David Peeters Gabriella Pizzuto Baris Serhan Linda Apse Florian Hesse Linh Hoang Phuong Hoang Yoko Igari Keerthana Kapiley Tamar Haupt-Khutsishvili Sara Kolding Katri Priiki Ieva Mačiukaitytė Vaisnavi Mohite Tiina Nahkola Sum Yi Tsoi Stefan Williams Shunei Yasuda Angelo Cangelosi Jon Andoni Duñabeitia Ramesh Kumar Mishra Roberta Rocca Jurģis Šķilters Mikkel Wallentin Eglė Žilinskaitė-Šinkūnienė Ozlem Durmaz Incel School of Psychology University of East Anglia Norwich UK. k.coventry@uea.ac.uk. School of Psychology University of East Anglia Norwich UK. Helmholtz Institute Department of Experimental Psychology Utrecht University Utrecht the Netherlands. Hanse-Wissenschaftskolleg Delmenhorst Germany. Department of English Friedrich-Schiller-Universität Jena Jena Germany. Department of Spanish Modern and Classic Philology University of the Balearic Islands Palma Spain. Language Acquisition and Language Processing Lab Department of Language and Literature Norwegian University of Science and Technology Trondheim Norway. Department of Spanish Language Linguistics and Literature Theory University of Seville Seville Spain. Institute of Estonian and General Linguistics University of Tartu Tartu Estonia. Centre for the Arts in Society Leiden University Leiden the Netherlands. Võro Institute Võru Estonia. Department of Linguistics University at Buffalo Buffalo NY USA. Danieli Telerobot Srl Genoa Italy. Istituto Italiano di Tecnologia (IIT) Genoa Italy. Paisii Hilendarski University of Plovdiv Plovdiv Bulgaria. Department of English University of Nevada Reno NV USA. Department of Slavonic Languages and Caucasus Studies Friedrich-Schiller-Universität Jena Jena Germany. Cognitive Science Department of Humanities Social and Political Sciences ETH Zürich Zürich Switzerland. Cognitive Science and Psycholinguistics Lab Central Department of Linguistics Tribhuvan University Kathmandu Nepal. Centre for Neural and Cognitive Sciences School of Medical Sciences University of Hyderabad Hyderabad India. Department of Communication and Cognition TiCC Tilburg University Tilburg the Netherlands. Max Planck Institute for Psycholinguistics Nijmegen the Netherlands. Department of Chemistry University of Liverpool Liverpool UK. Department of Computer Science University of Manchester Manchester UK. Laboratory for Perceptual and Cognitive Systems Faculty of Computing University o

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Incident detection based on mobile crowd sensing for smart city

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Journal of computers (Taiwan) 2019年第1期30卷 96-104页

作者： Zhang, Peng Zhang, Zhenjiang Chao, Han-Chieh Department of Electronic and Information Engineering Key Laboratory of Communication and Information Systems Beijing Municipal Commission of Education Beijing Jiaotong University Beijing100044 China Department of Software Engineering Key Laboratory of Communication and Information Systems Beijing Municipal Commission of Education Beijing Jiaotong University Beijing100044 China Department of Electrical Engineering National Dong Hwa University Hualien97401 Taiwan School of Information Science and Engineering Fujian University of Technology Fuzhou350118 China School of Mathematics and Computer Science Wuhan Polytechnic University Wuhan430023 China Department of Computer Science and Information Engineering National Ilan University Yilan County260 Taiwan

In recent years, mobile devices have taken a significant role in improving the quality of people’s life. In order to enhance the usability of those devices, more and more sensors have been built in. Furthermore, the data storage and data processing capacity are becoming larger and larger. To capture more information about the city conditions and make full use of the computing resource, mobile crowd sensing has been proposed. Incident detection is an important component of the safety monitoring system, however, existing incident detection methods are mostly based on computer vision which is vulnerability to environmental impacts. This paper proposes an automatic incident detection model based on Mobile Crowd Sensing to deal with the problem above. The incident detection algorithm in the model is based on the human activity recognition and the crowd density. The simulation results show that this model is feasible and effective. 2019 © computer Society of the Republic of China. All Rights Reserved.

关键词： Environmental impact

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Understanding deep neural network predictions for medical imaging applications

arXiv

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arXiv 2019年

作者： Narayanan, Barath Narayanan de Silva, Manawaduge Supun Hardie, Russell C. Kueterman, Nathan K. Ali, Redha Department of Electrical and Computer Engineering University of Dayton 300 College Park DaytonOH45469 United States Sensors and Software Systems Division University of Dayton Research Institute 1700 South Patterson Blvd. DaytonOH45409 United States

computer-aided detection has been a research area attracting great interest in the past decade. Machine learning algorithms have been utilized extensively for this application as they provide a valuable second opinion to the doctors. Despite several machine learning models being available for medical imaging applications, not many have been implemented in the real-world due to the uninterpretable nature of the decisions made by the network. In this paper, we investigate the results provided by deep neural networks for the detection of malaria, diabetic retinopathy, brain tumor, and tuberculosis in different imaging modalities. We visualize the class activation mappings for all the applications in order to enhance the understanding of these networks. This type of visualization, along with the corresponding network performance metrics, would aid the data science experts in better understanding of their models as well as assisting doctors in their decision-making process. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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Influence of Network Speed on Structured Query Language (SQL) Database Data Transmission Performance in an Internet of Things (IoT) Sensing Device on Single Board computers (SBC)

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IOP Conference Series: Materials Science and engineering 2019年第1期551卷

作者： A Nor Azhar S Nur Ayuni Hasna AH Roslina Z Fauziah M Rahmah Department of Computer Science Department of Computer Systems & Networking Department of Software Engineering Department of Graphic & Multimedia Technology Faculty of Computer Systems & Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Gambang 26300 Kuantan Pahang Malaysia

One of the crucial elements in an Internet of Things (IoT) environment is a database. IoT performance will be at stake if the wrong database is adopted. In this research, three Structured Query Language (SQL) databases were tested against multiple network speeds in an IoT device. Single board computers (SBC) were used as a media of testing instead of an ordinary computer. A controlled wireless sensor network (WSN) was developed with several uniform constants and variable network speeds. A new data transmission rate equation also was proposed and tested. From the result, it was found that not all SQL databases can cater IoT devices. Some of them showed that performance decreased along with network speed. The correlation, between 0.90 and 0.96, proved the strong influence between the research subjects. In addition, file-type database is the best option available for SQL-wise IoT storage.

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Development of semantic web application architecture for natural language based querying 7

Development of semantic web application architecture for nat...

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7th Turkish National software Architecture Conference, UYMK 2018

作者： Tasar, Ceren Ocal Komesli, Murat Unalir, Murat Osman Yasar University Software Engineering Department Universite Cad. 35 Bornova Izmir35100 Turkey Yasar University Management Information Systems Department Universite Cad. 35 Bornova Izmir35100 Turkey Ege University Computer Engineering Department Universite Cad. 9 BornovaIzmir35100 Turkey

With the developing technology and increased demand on practical usage of knowledge, users require to interact with systems by using natural language. Researchers discover the necessity of natural language queries should be converted to machine understandable format to meet the requirement of users. The necessity of the conversion triggered the researches on studies on question answering systems that is one of the systems mostly interact with natural language queries. For question answering systems that utilizes structural knowledge sources, understanding user intention accurately consists of the processes of natural language processing, representing the user intention and forming structured query to generate the answer. A technique and an architecture to convert natural language query to ontology query language by utilizing from both linguistic and semantic technologies are proposed in this study. Automatic conversion of an unstructured natural language query to a structured ontology query language SPARQL and process of producing answer over linked data are explained in the proposed technique and architecture. A different approach other than the related studies is followed in terms of defining a "Query Semantization" layer in the proposed architecture and developing a natural language aware ontology for the technique proposed. Contribution to the literature is expected by combining natural language processing technique and semantic web technologies with a different approach. © 2019 CEUR Workshop *** Rights Reserved.

关键词： Ontology

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Research of modern opportunities for obtaining the grant support for innovative projects financing

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IOP Conference Series: Earth and Environmental Science 2021年第2期677卷

作者： A L Zolkin T G Aygumov A I Pakhomova V V Bobkov Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics L. Tolstogo Street 23 Samara 443010 Russia Department of computer engineering software and automated systems Dagestan State Technical University I. Shamyl Street 70 Makhachkala 367000 Russia Department of Economics and management Institute of service and entrepreneurship (branch) of DSTU in Shakhty Shevchenko Street 147 Shakhty 346500 Russia Department of Physical Education and Sports Gubkin Russian State University of Oil and Gas Leninsky prospect 65 Moscow 119991 Russia

This paper examines innovative, including social entrepreneurship and modern opportunities for obtaining grant support for financing innovative projects, including social ones. The possibility of receiving grants from various funds is being considered. Detailed attention is paid to the stages of project development for drawing up an application for grant funding. Attention is drawn to certain nuances in the writing and processing of grant applications. We also conduct research on current conditions and factors that influence the development of innovative entrepreneurship, and compare Russian indicators with foreign ones. Detailed attention is paid to economic and innovative conditions, educational factors, measures to promote competition and tax incentives.

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The occupation kernel method for nonlinear system identification

arXiv

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arXiv 2019年

作者： Rosenfeld, Joel A. Russo, Benjamin Kamalapurkar, Rushikesh Johnson, Taylor T. Department of Mathematics and Statistics University of South Florida TampaFL33620 United States Department of Mathematics Farmingdale State College FarmingdaleNY11735 United States Department of Mechanical and Aerospace Engineering Oklahoma State University StillwaterOK74078 United States Institute for Software Integrated Systems Department of Electrical Engineering and Computer Science Vanderbilt University NashvilleTN37212 United States

This manuscript presents a novel approach to nonlinear system identification leveraging densely defined Liouville operators and a new "kernel" function that represents an integration functional over a reproducing kernel Hilbert space (RKHS) dubbed an occupation kernel. The manuscript thoroughly explores the concept of occupation kernels in the contexts of RKHSs of continuous functions, and establishes Liouville operators over RKHS where several dense domains are found for specific examples of this unbounded operator. The combination of these two concepts allow for the embedding of a dynamical system into a RKHS, where function theoretic tools may be leveraged for the examination of such systems. This framework allows for trajectories of a nonlinear dynamical system to be treated as a fundamental unit of data for nonlinear system identification routine. The approach to nonlinear system identification is demonstrated to identify parameters of a dynamical system accurately, while also exhibiting a certain robustness to noise. Copyright © 2019, The Authors. All rights reserved.

关键词： Employment

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Empirical topological investigation of practical supply chains based on complex networks

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Chinese Physics B 2017年第11期26卷 144-150页

作者：廖好沈婧吴兴桐陈博奎周明洋 National Engineering Laboratory for Big Data Computing Systems Guangdong Province Key Laboratory of Popular High Performance ComputersCollege of Computer Science and Software Engineering Shenzhen University Department of Computer Science School of Computing National University of Singapore

The industrial supply chain networks basically capture the circulation of social resource, dominating the stability and efficiency of the industrial system. In this paper, we provide an empirical study of the topology of smartphone supply chain network. The supply chain network is constructed using open online data. Our experimental results show that the smartphone supply chain network has small-world feature with scale-free degree distribution, in which a few high degree nodes play a key role in the function and can effectively reduce the communication cost. We also detect the community structure to find the basic functional unit. It shows that information communication between nodes is crucial to improve the resource utilization. We should pay attention to the global resource configuration for such electronic production management.

关键词： China supply chain networks complex networks data science network science

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Lockout-Tagout Ransomware: A Detection Method for Ransomware using Fuzzy Hashing and Clustering

Lockout-Tagout Ransomware: A Detection Method for Ransomware...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Nitin Naik Paul Jenkins Jonathan Gillett Haralambos Mouratidis Kshirasagar Naik Jingping Song School of Computing University of Portsmouth United Kingdom Faculty of Science and Technology Bournemouth University United Kingdom Centre for Secure Intelligent and Usable Systems University of Brighton United Kingdom Department of Electrical and Computer Engineering University of Waterloo Canada Software College Northeastern University China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

Ransomware attacks are a prevalent cybersecurity threat to every user and enterprise today. This is attributed to their polymorphic behaviour and dispersion of inexhaustible versions due to the same ransomware family or threat actor. A certain ransomware family or threat actor repeatedly utilises nearly the same style or codebase to create a vast number of ransomware versions. Therefore, it is essential for users and enterprises to keep well-informed about this threat landscape and adopt proactive prevention strategies to minimise its spread and affects. This requires a technique to detect ransomware samples to determine the similarity and link with the known ransomware family or threat actor. Therefore, this paper presents a detection method for ransomware by employing a combination of a similarity preserving hashing method called fuzzy hashing and a clustering method. This detection method is applied on the collected WannaCry/WannaCryptor ransomware samples utilising a range of fuzzy hashing and clustering methods. The clustering results of various clustering methods are evaluated through the use of the internal evaluation indexes to determine the accuracy and consistency of their clustering results, thus the effective combination of fuzzy hashing and clustering method as applied to the particular ransomware corpus. The proposed detection method is a static analysis method, which requires fewer computational overheads and performs rapid comparative analysis with respect to other static analysis methods.

关键词： Ransomware Clustering methods Indexes Cryptography Engines Syntactics

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Towards Eliciting and Analyzing Security Requirements Using Ontologies through Use Case Scenarios (Work-in-Progress)

Towards Eliciting and Analyzing Security Requirements Using ...

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International Conference on software Security and Assurance (ICSSA)

作者： Omar Ochoa Jessica Steinmann Yevgeniy Lischuk Department of Electrical Computer Software & Systems Engineering Embry-Riddle Aeronautical University Daytona Beach FL USA

ISBN: (数字)9781538692103

ISBN: (纸本)9781538692110

As our reliance on large, complex and ubiquitous software system increases, so does the devastating consequences that a cyberattack can have to modern society. Building secure software systems requires a greater need for secure software engineering approaches that can detect and address security vulnerabilities at the earliest stages of the software development life cycle. This paper presents an approach to facilitate the elicitation of cybersecurity requirements based on enhancing the widely adopted technique of use case modeling by incorporating the use of an ontology. The ontology will model the semantic relationship of cybersecurity requirements. Utilizing this ontology, we propose an approach that can be used to reuse and share cybersecurity requirements, providing a potential for the rapid discovery and correction of software vulnerabilities in the development process.

关键词： Ontologies software systems Cyberattack Authentication

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