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Research on Lightweight Sensing technology Based on Single-Antenna Multicarrier

IEEE Internet of Things Journal 2025年第12期12卷 20678-20694页

作者： Jiang, Yu Zhu, Di Wang, Jiadong Hu, Aiqun Southeast University School of Cyber Scienc and Engineering Purple Mountain Laboratories Nanjing210096 China Key Laboratory of Computer Network Technology of Jiangsu Province Nanjing210096 China Southeast University Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Southeast University School of Cyber Science and Engineering Nanjing210096 China Southeast University School of Cyber Science and Engineering School of Information Science and Engineering Nanjing210096 China Southeast University State Key Laboratory of Mobile Communication Nanjing210096 China

Channel State Information (CSI) serves as a critical indicator of wireless signal conditions and is widely regarded by researchers for its sensitivity in detecting changes within the channel. However, traditional sensing technologies often require substantial data and intricate learning algorithms, highlighting an urgent need for advancements in lightweight sensing technologies. These technologies should leverage simpler terminal devices, reduced data volumes, and more straightforward classification algorithms to achieve sensing capability that are comparable to those offered by more complex and established methods. This paper concentrates on the lightweight application of wireless sensing and encompasses the following key contributions: 1) The development of a lightweight sensing model utilizing a single-antenna multicarrier system, which introduces a CSI ratio model that adapts multi-antenna techniques for single-antenna settings;2) The enhancement of feature stability through the introduction of a complex-plane fitting method using artificial vector, alongside a dual receiver based method for cross-scene feature generation aimed at producing stable and high-quality auxiliary features. Experimental results show that the feature extraction capability of the single-antenna multicarrier CSI ratio model is close to that of traditional multi-antenna scheme. On the gait dataset, when the enhanced CSI ratio is used as a feature, the accuracy is nearly 100%, surpassing the 93% accuracy of the original amplitude feature. On the gesture dataset, the combination of the enhanced CSI ratio and PEI features achieves an accuracy of 96%, which is superior to using the original CSI amplitude feature alone. An analysis of resource consumption shows that the lightweight SVM model incurs very low computational overhead during decision-making, validating the potential of this scheme in terms of efficiency and practical application. © 2014 IEEE.

关键词： Communication channels (information theory)

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Fraud Detection and Prevention in E-Commerce: Machine Learning Approaches to Secure Transactions 1

Fraud Detection and Prevention in E-Commerce: Machine Learni...

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1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Srinivas, Madhira Kilaru, Mrudula Jain, Divya Sidhu, Kawerinder Singh Department of Computer Science & Engineering - Data Scienc Cheeryala Hyderabad501301 India Siddhartha Academy of Higher Education Velagapudi Ramakrishna Siddhartha School of Engineering India Jaypee University of Engineering and Technology Department of Mathematics Madhya Pradesh Guna473226 India Uttaranchal Institute of Management Uttaranchal University Uttarakhand Dehradun India

ISBN: (纸本)9798331518578

E-commerce has grown as a leading marketplace for world trade, but this market has been contaminated by new risks like fraud. Some of the past techniques of detecting fraud do not do well in handling new methods of fraud in the market. The purpose of this research is to understand the offers of the ML approaches for increasing the efficiency of the fraud detection and prevention in e-Commerce processer. This study shows the utility of using different types of the ML solution alone and in comparison, to one another for real-time cyber fraud identification by demonstrating how and why their false positives and overall effectiveness are lower than other methods, as well as how the models adapt to new tactics. Issues like quality of data used, bias in either selection or process of the algorithm are also covered. © 2025 IEEE.

关键词： Marketplaces

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Utilizing Quantitative Data science Salary Analysis to Predict Job Salaries 2

Utilizing Quantitative Data Science Salary Analysis to Predi...

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2nd International Conference on Innovative Sustainable Computational Technologies, CISCT 2022

作者： Kaur, Arshdeep Verma, Deval Kaur, Navneet Chandigarh University University of Science Punjab Mohali India Bennett University School of Computer Scienc Engineering and Technology Times Group Greater Noida201310 India

ISBN: (纸本)9781665474160

The primary goal of this article is to illustrate the differences in salaries among the many fields of data science, which were examined using survey data from the years 2020- 2021. There are many work opportunities in the field of data science. However, a variety of jobs, around 43 different kinds of employments are in the industry. The variations further depend on the skills or software that are increasing their values in the field. The research is based on a data set taken from an open-source - "Kaggle"as well as online survey for various sites. SQL (60%), Excel, R, and Python (90%) are among the technologies remaining at the top of the list. According to recent reports, IT employees in the US are compensated the same salaries as healthcare workers. Some cloud computing services (such as AWS and involve a demand of 40%) have attracted significant attention. The ecommerce department has given the highest hike which is around 15% in the last two years. In fact, women enjoy equal involvement in the field of data science that is around 40% better than other fields, which is also covered in this article. Despite equal involvement, women are paid less than men. To explain more specifically, visualization is the medium which is used as images works more efficiently than words. © 2022 IEEE.

关键词： Visualization

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Transforming Cybersecurity in the Digital Era: The Power of AI 2

Transforming Cybersecurity in the Digital Era: The Power of ...

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2nd International Conference on Cyber Resilience, ICCR 2024

作者： Mahfuri, Mahmoud Ghwanmeh, Sameh Almajed, Rsha Alhasan, Waseem Salahat, Mohammed Lee, Jin Hie Ghazal, Taher M. International University For Science And Technology Computer And Information Technology Department Damascus Syria American University In The Emirates Department Of Computer Scienc Dubai United Arab Emirates School Of Computer Science And Informatics De Montfort University Dubai Dubai United Arab Emirates College Of Engineering And Technology University Of Science And Technology Of Fujairah Fujairah United Arab Emirates Miracle Clinic Seoul Korea Republic of Khalifa University Centre For Cyber Physical Systems Computer Science Department United Arab Emirates Center For Cyber Security Faculty Of Information Science And Technology Selangor Bangi43600 Malaysia

ISBN: (纸本)9798350394962

In the midst of the digital revolution of the 21st century, cybersecurity has come to be a primary social situation, requiring revolutionary and Innovative solution. To find the proper answer for this pressing demand, AI (AI) has developed as an innovative catalyst that has fundamentally transformed the cybersecurity landscape. The power of AI is exemplified by its ability to process and interpret large and heterogeneous cybersecurity data sets optimizing critical functions such as threat detection, asset prioritization, and vulnerability management beyond human capabilities swiftly and accurately. This transformation is redefining our cybersecurity approach. This paper presents a full exploration of AI's extreme influence on cybersecurity, delving deep into how AI tools not only enhance but often surpass human-mediated processes. By unraveling the intricacies of integrating AI into the realm of cybersecurity, we vividly illustrate AI's potential to anticipate, detect, and proactively mitigate cyber threats, empowering organizations to bolster their digital security. However, it's vital to recognize the essential difficulties of AI. We underline the critical necessity for non-stop human administration and involvement to confirm that cybersecurity processes are in proportion and powerful. Additionally, we mention the probable ethical concerns and underscore the importance of strong authority structures to accelerate accountable and transparent AI usage in cybersecurity. This paper elucidates how AI is revolutionizing cybersecurity techniques, contributing to a more secure and greater secure digital future. It additionally lays the base for current investigation and discourse on the role of AI in cybersecurity - a conversation of growing importance in our unexpectedly advancing digital age. © 2024 IEEE.

关键词： Cybersecurity

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Usability Evaluation of Kids' Learning Apps 2

Usability Evaluation of Kids' Learning Apps

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2nd International Conference on Business Analytics for technology and Security, ICBATS 2023

作者： Ibrahim, Amer Al-Rajab, Murad Hamid, Khalid Aqeel, Muhamamd Muneer, Salman Parveen, Mehvish Saleem, Maryam American University in the Emirates College of Computer and Information Technology Dubai United Arab Emirates Abu Dhabi University Computer Scienc and IT College of Engineering United Arab Emirates Superior University Department of Computer Science Lahore Pakistan Superior University Department of Software Engineering Lahore Pakistan NCBA&E School of Computer Science Lahore Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan NCBAE School of Computer Science Lahore Pakistan

ISBN: (纸本)9798350335644

The main objective of learning applications is to use modern electronic technologies to impart knowledge, communicate knowledge, and Direct learning models with their learning activities in a timely and effective manner. The preponderance of the apps were designed to up-skill the kids in the fundamentals of letters and numbers. Generally, they were grounded and practice skills in nature, based on a lack of abilities in critical thinking, favoring parrot-fashion skills, and contributing to a deep conceptual comprehension of more specific concepts are unable. By using appropriate evaluation methodologies, the purposed study observes essential characteristics and aspects that affect the usability of interfaces. An evaluation of the app's features will figure out to ensure user contentment. When a kid interacts with a learning interface, the ease of use provided by the interface is validated. Because a large number of the apps were designed to train kids' fundamentals of alphabetic and numeric. The focus of this research is to see whether self-proclaimed learning apps for kids are built according to developmentally appropriate standards to help kids in formal and informal learning settings develop socially, emotionally, and academically. © 2023 IEEE.

关键词： Learning systems

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Fraud Detection and Prevention in E-Commerce: Machine Learning Approaches to Secure Transactions

Fraud Detection and Prevention in E-Commerce: Machine Learni...

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Advances in computer science, Electrical, Electronics, and Communication Technologies (CE2CT), International Conference on

作者： Madhira Srinivas Mrudula Kilaru Divya Jain Kawerinder Singh Sidhu Department of Computer Science & Engineering - Data Scienc Geethanjali College of Engineering & Technology (GCET) Cheeryala Hyderabad India Siddhartha Academy of Higher Education Velagapudi Ramakrishna Siddhartha School of Engineering Department of Mathematics Jaypee University of Engineering and Technology Guna Madhya Pradesh Uttaranchal Institute of Management l Uttaranchal University Dehradun Uttarakhand India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

关键词： Machine learning algorithms Prevention and mitigation Machine learning Real-time systems Fraud Pattern recognition Electronic commerce Stakeholders Security Unsupervised learning

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Utilizing Quantitative Data science Salary Analysis to Predict Job Salaries

Utilizing Quantitative Data Science Salary Analysis to Predi...

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International Conference on Innovative Sustainable Computational Technologies (CISCT)

作者： Arshdeep Kaur Deval Verma Navneet Kaur University of Science Chandigarh University Mohali Punjab India School of Computer Scienc Engineering and Technology Bennett University Greater Noida

ISBN: (纸本)9781665474177

The primary goal of this article is to illustrate the differences in salaries among the many fields of data science, which were examined using survey data from the years 2020– 2021. There are many work opportunities in the field of data science. However, a variety of jobs, around 43 different kinds of employments are in the industry. The variations further depend on the skills or software that are increasing their values in the field. The research is based on a data set taken from an open-source - "Kaggle" as well as online survey for various sites. SQL (60%), Excel, R, and Python (90%) are among the technologies remaining at the top of the list. According to recent reports, IT employees in the US are compensated the same salaries as healthcare workers. Some cloud computing services (such as AWS and involve a demand of 40%) have attracted significant attention. The ecommerce department has given the highest hike which is around 15% in the last two years. In fact, women enjoy equal involvement in the field of data science that is around 40% better than other fields, which is also covered in this article. Despite equal involvement, women are paid less than men. To explain more specifically, visualization is the medium which is used as images works more efficiently than words.

关键词： Industries Cloud computing Pandemics Instruments Medical services Data science Software

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Grey Wolf algorithm based on S-function and particle swarm optimization 2

Grey Wolf algorithm based on S-function and particle swarm o...

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2019 2nd International Conference on computer Information science and Artificial Intelligence, CISAI 2019

作者： Liu, Chenyang Wang, Yongli School of Computer Science and Engineering Nanjing University of Scienc and Technology Nanjing210094 China

Based on the analysis of the shortcomings of the grey wolf optimization algorithm, an improved grey wolf optimization algorithm (SGWO) is proposed. The algorithm uses the convergence factor based on S-function change to balance the global search and local search ability of the algorithm. At the same time, the proportion weight based on Euclidean distance of step size and the individual optimal position of the particle swarm optimization algorithm are introduced to update the grey wolf position, thus speeding up the convergence speed of the algorithm to 8. The simulation results of three classical test functions show that the SGWO algorithm has higher accuracy and better ***. © Published under licence by IOP Publishing Ltd.

关键词： Particle swarm optimization (PSO)

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Usability Evaluation of Kids’ Learning Apps

Usability Evaluation of Kids’ Learning Apps

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Business Analytics for technology and Security (ICBATS), International Conference on

作者： Amer Ibrahim Murad Al-Rajab Khalid Hamid Muhamamd Aqeel Salman Muneer Mehvish Parveen Maryam Saleem College of Computer and Information Technology American University in the Emirates Dubai United Arab Emirates Assistant Professor Computer Scienc and IT College of Engineering Abu Dhabi University Department of Computer Science Superior University Lahore Pakistan Department of Software Engineering Superior University Lahore Pakistan School of Computer Science NCBA&E Lahore Pakistan Applied Science Research Center Applied Science Private University Amman Jordan School of Computer Science NCBAE Lahore Pakistan

The main objective of learning applications is to use modern electronic technologies to impart knowledge, communicate knowledge, and Direct learning models with their learning activities in a timely and effective manner. The preponderance of the apps were designed to up-skill the kids in the fundamentals of letters and numbers. Generally, they were grounded and practice skills in nature, based on a lack of abilities in critical thinking, favoring parrot-fashion skills, and contributing to a deep conceptual comprehension of more specific concepts are unable. By using appropriate evaluation methodologies, the purposed study observes essential characteristics and aspects that affect the usability of interfaces. An evaluation of the app's features will figure out to ensure user contentment. When a kid interacts with a learning interface, the ease of use provided by the interface is validated. Because a large number of the apps were designed to train kids’ fundamentals of alphabetic and numeric. The focus of this research is to see whether self-proclaimed learning apps for kids are built according to developmentally appropriate standards to help kids in formal and informal learning settings develop socially, emotionally, and academically.

关键词： Electronic learning User interfaces Security Usability Standards Business

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Transforming Cybersecurity in the Digital Era: The Power of AI

Transforming Cybersecurity in the Digital Era: The Power of ...

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Cyber Resilience (ICCR), International Conference on

作者： Mahmoud Mahfuri Sameh Ghwanmeh Rsha Almajed Waseem Alhasan Mohammed Salahat Jin Hie Lee Taher M. Ghazal Computer and information Technology Department International University for Science and Technology Damascus Syria Department of Computer Scienc American University in the Emirates Dubai UAE School of Computer Science and Informatics De Montfort University Dubai Dubai United Arab Emirates College of Engineering and Technology University of Science and Technology of Fujairah Fujairah UAE Miracle Clinic Seoul S. Korea Computer Science Department Centre for Cyber Physical Systems Khalifa University Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia (UKM) Bangi Selangor Malaysia

ISBN: (数字)9798350394962

ISBN: (纸本)9798350394979

In the midst of the digital revolution of the 21st century, cybersecurity has come to be a primary social situation, requiring revolutionary and Innovative solution. To find the proper answer for this pressing demand, AI (AI) has developed as an innovative catalyst that has fundamentally transformed the cybersecurity landscape. The power of AI is exemplified by its ability to process and interpret large and heterogeneous cybersecurity data sets optimizing critical functions such as threat detection, asset prioritization, and vulnerability management beyond human capabilities swiftly and accurately. This transformation is redefining our cybersecurity approach. This paper presents a full exploration of AI's extreme influence on cybersecurity, delving deep into how AI tools not only enhance but often surpass human-mediated processes. By unraveling the intricacies of integrating AI into the realm of cybersecurity, we vividly illustrate AI's potential to anticipate, detect, and proactively mitigate cyber threats, empowering organizations to bolster their digital security. However, it's vital to recognize the essential difficulties of AI. We underline the critical necessity for non-stop human administration and involvement to confirm that cybersecurity processes are in proportion and powerful. Additionally, we mention the probable ethical concerns and underscore the importance of strong authority structures to accelerate accountable and transparent AI usage in cybersecurity. This paper elucidates how AI is revolutionizing cybersecurity techniques, contributing to a more secure and greater secure digital future. It additionally lays the base for current investigation and discourse on the role of AI in cybersecurity—a conversation of growing importance in our unexpectedly advancing digital age.

关键词： Ethics Scalability Pressing Organizations Oral communication Information age Threat assessment

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