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IEEE Symposium on Computers and Communications (ISCC)

作者： Ahmed Abdelmaguid Marwan Torki Ayman Khalafallah Dept. of Comp. and Sys. Engineering Alexandria University Alexandria Egypt

ISBN: (数字)9798350354232

ISBN: (纸本)9798350354249

With the rise of social media, accurately identifying genders in the text has become crucial for various domains. It is used in a wide range of academic/commercial applications such as personalization of user experiences, analyzing and interpreting text more accurately in Natural Language Understanding (NLU), and identifying and mitigating biases in datasets and models. The importance of this task is reflected in the extensive research and contribution to it, specifically in Arabic text. Existing work addresses this problem as a sub-task of the Author Profiling task, by detecting the author’s gender using multiple texts of the same author. Although current approaches achieve satisfactory results, they still fall behind in the detection of genders based on a single short sentence. In this paper, we provide a newly tailored dataset, AraEGI, to tackle Gender Identification, capable of reaching robust results on the identification of gender in tweets. Our dataset consists of 3 sets, with tweet-level labels showcasing the genders of both the speaker and the listener. We experimented on our dataset using the latest Arabic transformer models to provide a benchmark for future research.

关键词： Computers Analytical models Social networking (online) Annotations Media Benchmark testing Transformers Natural language processing

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Formal Verification for Security Technologies in the Blockchain with Artificial Intelligence: A survey

Formal Verification for Security Technologies in the Blockch...

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2022 Innovations in Intelligent sys.ems and Applications Conference, ASYU 2022

作者： Ilgi, Galip Savas Kayali, Devrim Olawale, Priscilla Demir Erdem, Binnur Dimililer, Kamil Kirsal-Ever, Yoney Near East University Information Sys. Engineering Dept. Nicosia Turkey Near East University Electrical & Electronic Engineering Dept. Nicosia Turkey Near East University Software Engineering Dept. Nicosia Turkey Near East University Automotive Engineering Dept. Nicosia Turkey

ISBN: (数字)9781665488945

ISBN: (纸本)9781665488945

Last two decades enhancements of the communication technologies have been interpreting the daily lives as well as the academia and multidisciplinary research fields. One of these enhancements is the blockchain technology which has become one of the most popular and attractive topics over the last five years. Blockchain technology has attracted more and more attention from academia and industry recently. Blockchain is defined as a list of data blocks as a publicly distributed ledger, which are linked together using cryptography. In this matter, cryptographic security issues have increased. In recent years, new, advanced intrusion detection and authentication/privacy protection techniques have been designed and developed. Diversity of computer security requirements results in introducing of different kinds of security models. In fact, each security model is an abstraction of a security policy. Formal Methods have a mathematical foundation, and thus, employs techniques and tools based on mathematics and mathematical logic that support the modelling, specification and verification of the sys.ems. This paper provides a critical and detailed review of the recent researches published in recent years in formal verification methods for communication security in blockchain with artificial intelligence applications. © 2022 IEEE.

关键词： Smart contract

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A One Inch in Diameter Point-of-Care Reader Head for the Measurement of Different Bio-Analytes Concentrations

A One Inch in Diameter Point-of-Care Reader Head for the Mea...

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2022 IEEE-EMB Special Topic Conference on Healthcare Innovations and Point of Care Technologies, HI-POCT 2022

作者： Tofighi Zavareh, Amir Serivuth Ko, Brian Horner, Richard Lewis, Cody Mcshane, Michael J. Texas AM University Dept. of Biomedical Engineering College StationTX United States Texas AM Engineering Experiment Station CTR. for Remote Health Tech. and Sys. College StationTX United States

ISBN: (纸本)9781665496155

Point of care (POC) devices facilitate access to rapid diagnostic information and play a crucial role in managing diseases. Combined with bio-sensors, POC devices are able to continuously measure the concentration of a variety of bioanalytes and mark the signs of abnormality. With the recent advancements in the state of the art electronics, miniaturized POC testing devices that have convenient wearable form factors are being materialized. A miniaturized cylindrical phosphorescent reader head with a diameter of only 25.4mm that is capable of measuring the concentration of different bio-analytes such as oxygen and glucose is reported in this paper. © 2022 IEEE.

关键词： Diagnosis

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Understanding Statistical Correlation of Application Security Vulnerability Data from Detection and Monitoring Tools 33

Understanding Statistical Correlation of Application Securit...

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33rd International Telecommunication Networks and Applications Conference, ITNAC 2023

作者： Kasturi, Santanam Li, Xiaolong Pickard, John Li, Peng Indiana State University Technology Management Terre Haute United States Indiana State University Dept. of Electronics and Computer Engineering Terre Haute United States East Carolina University Dept. of Technology Sys Greenville United States East Carolina University Dept. of Technology Systems Greenville United States

ISBN: (纸本)9798350317138

Vulnerability data gathered from multiple detection and monitoring capabilities at different layers of an application using a time-series analysis will provide value and insights by doing a statistical correlation with attack requests observed using a Web Application Firewall (WAF) monitoring solution. Static Analysis Security Testing, Software Composition Analysis, Dynamic Analysis Security Testing (DAST), Application Ethical Hack, Application Programming Interface (API) testing are the tests / scans that have been used to gather vulnerability data for this study. Correlations can further help track abnormal transaction paths if we follow specific ones pointed out by the statistical analysis for those requests that are not blocked by the rules and are allowed as valid transactions to pass through. This provides a narrowed down focus on the convergence of observability and security, critical to realizing a near-real time rapid action. Observations must continue for many days as a time series ensuring consistency and reliability in data collections and analysis. Multiple applications must be observed in a similar manner for ensuring validity of the process for analysis. Also, gathering sufficient data that is large enough to represent a reasonable population of web applications within an organization is a significant factor in achieving reliable correlation. Applying Pearson Correlation (or Spearman Correlation for distributions that are not normal) technique provides insight into Significance (two-tailed) as to whether a correlation is present over large number of data points. Results of analysis show evidence of correlations among specific attack requests monitored by the WAF and corresponding vulnerabilities in applications, detected using one or more methods. This is significant to looking for more insights into how these correlations can further explored into predicting attack patterns based on existing vulnerabilities. © 2023 IEEE.

关键词： Time series analysis

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Large Scale IoT Training using Arduino 11

Large Scale IoT Training using Arduino

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11th IEEE International Conference on Teaching, Assessment and Learning for engineering, TALE 2022

作者： Kushalkar, Rajesh Venkat, Nirmala Karmali, Firuza Karmali, Nagesh Kumar, Sudhakar Moudgalya, Kannan M. Sharma, G.V.V. IIT Bombay Dept. of Comp. Science & Engg. Mumbai India IIT Bombay Dept. of Chemical Engineering Mumbai India IIT Bombay Dept. of Sys. & Cont. Engg. Mumbai India IIT Bombay Dept. of Chem. Engg. Mumbai India IIT Hyderabad Dept. of Elec. Engg. Mumbai India

ISBN: (纸本)9781665491174

This article explains the self-learning Spoken Tutorials on the popular open source microcontroller Arduino UNO. It introduces freely downloadable books that explain how Arduino UNO can be controlled from Scilab, Xcos, Python, Julia, and OpenModelica. Using these, 1,500 college teachers and 75,000 students have been trained. An Arduino Cloud is created to make this experience available also to those who do not have access to the Arduino hardware. © 2022 IEEE.

关键词： Python

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Optimal Sensor Placement for Atmospheric Inverse Modelling

Optimal Sensor Placement for Atmospheric Inverse Modelling

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Liu, Xinchao Yeo, Kyongmin Klein, Levente Hwang, Youngdeok Phan, Dzung Liu, Xiao University of Arkansas Dept. of Industrial Engineering FayettevilleAR72702 United States Thomas J. Watson Research Center Ibm Yorktown HeightsNY10598 United States City University of New York Dept. of Info. Sys. and Statistics Baruch College New YorkNY10010 United States

ISBN: (纸本)9781665480451

For large scale monitoring of the environment, the number of possible pollution sources can be larger than the number of sensors. For optimal sensor placement under various wind fields in source inversion problems, this paper proposes a framework under non-Gaussian priors for the detection and inversion estimate of emission rates. The optimization framework with non-Gaussian prior utilizes a bi-level optimization expression with inner quadratic programming. The proposed truncated Gaussian prior is to incorporate non-negativity of emission rates, but it poses a challenge in optimization. We preliminarily investigate the bi-level optimization with a Gaussian plume model example. The Karush-Kuhn-Tucker conditions of the inner quadratic programming are considered for solving the bi-level optimization. The efficiency of the proposed optimization framework is demonstrated by numerical results to optimally place sensors and quantify emission rates. © 2022 IEEE.

关键词： Quadratic programming

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Egyptian sign language recognition using CNN and LSTM

arXiv

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arXiv 2021年

作者： Elhagry, Ahmed Adel Gomaa Elrayes, Rawan Gla Zamel, Amr Helmy, Ahmed Comp. and Sys. Dept. Faculty of Engineering Zagazig University Egypt

Sign language is a set of gestures that deaf people use to communicate. Unfortunately, normal people don't understand it, which creates a communication gap that needs to be filled. Because of the variations in (Egyptian Sign Language) ESL from one region to another, ESL provides a challenging research problem. In this work, we are providing applied research with its video-based Egyptian sign language recognition sys.em that serves the local community of deaf people in Egypt, with a moderate and reasonable accuracy. We present a computer vision sys.em with two different neural networks architectures. The first is a Convolutional Neural Network (CNN) for extracting spatial features. The CNN model was retrained on the inception mod. The second architecture is a CNN followed by a Long Short Term Memory (LSTM) for extracting both spatial and temporal features. The two models achieved an accuracy of 90% and 72%, respectively. We examined the power of these two architectures to distinguish between 9 common words (with similar signs) among some deaf people community in Egypt. © 2021, CC BY.

关键词： Computer vision

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Understanding Statistical Correlation of Application Security Vulnerability Data from Detection and Monitoring Tools

Understanding Statistical Correlation of Application Securit...

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Australasian Telecommunication Networks and Applications Conference, ATNAC

作者： Santanam Kasturi Xiaolong Li John Pickard Peng Li Technology Management Indiana State University Terre Haute USA Dept. of Electronics and Computer Engineering Indiana State University Terre Haute USA Dept. of Technology Sys East Carolina University Greenville USA Dept. of Technology Systems East Carolina University Greenville USA

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Optimal Sensor Placement for Atmospheric Inverse Modelling

Optimal Sensor Placement for Atmospheric Inverse Modelling

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IEEE International Conference on Big Data

作者： Xinchao Liu Kyongmin Yeo Levente Klein Youngdeok Hwang Dzung Phan Xiao Liu Dept. of Industrial Engineering University of Arkansas Fayetteville AR USA Thomas J. Watson Research Center IBM NY USA Dept. of Info. Sys. and Statistics Baruch College City University of New York New York NY USA

ISBN: (纸本)9781665480468

For large scale monitoring of the environment, the number of possible pollution sources can be larger than the number of sensors. For optimal sensor placement under various wind fields in source inversion problems, this paper proposes a framework under non-Gaussian priors for the detection and inversion estimate of emission rates. The optimization framework with non-Gaussian prior utilizes a bi-level optimization expression with inner quadratic programming. The proposed truncated Gaussian prior is to incorporate non-negativity of emission rates, but it poses a challenge in optimization. We preliminarily investigate the bi-level optimization with a Gaussian plume model example. The Karush–Kuhn–Tucker conditions of the inner quadratic programming are considered for solving the bi-level optimization. The efficiency of the proposed optimization framework is demonstrated by numerical results to optimally place sensors and quantify emission rates.

关键词： Sensor placement Inverse problems Atmospheric modeling Toy manufacturing industry Sensor phenomena and characterization Big Data Data models

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Large Scale IoT Training using Arduino

Large Scale IoT Training using Arduino

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IEEE International Conference on Teaching, Assessment and Learning for engineering (TALE)

作者： Rajesh Kushalkar Nirmala Venkat Firuza Karmali Nagesh Karmali Sudhakar Kumar Kannan M. Moudgalya G. V. V. Sharma Dept. of Comp. Science & Engg. IIT Bombay Mumbai India Dept. of Chemical Engineering IIT Bombay Mumbai India Dept. of Sys. & Cont. Engg. IIT Bombay Mumbai India Dept. of Chem. Engg. IIT Bombay Mumbai India Dept. of Elec. Engg. IIT Hyderabad Mumbai India

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