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Advancements in User Security: Enhancing Usability with Graphical Password Authentication

Advancements in User Security: Enhancing Usability with Grap...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Harisha Sandhya Ramesh Naik Shettigar Sarvani Vasudeva K Shrilakshmi Vaishnavi Kothwal Dept. of Computer Science & Engineering Sahyadri College of Engineering & Management Mangalore Karnataka India

Text-based password authentication is a common method used to verify the identity of users who are trying to access a secure system or service. In order to use this authentication method, the user must input a password or other secret phrase that is then compared to a server-side copy of the same password. Access is given if the password typed matches the one saved. Graphical password authentication is a type of user authentication that involves using images or visual elements instead of alphanumeric characters to verify the identity of the user. Unlike traditional text-based passwords, graphical passwords offer an intuitive and user-friendly way of authentication, as they rely on the user's ability to remember pictures, shapes, and patterns. This technology has been developed to address the limitations of traditional text-based passwords, such as the difficulty of creating and remembering complex passwords, and the vulnerability to brute-force attacks. Compared to conventional text-based passwords, graphical password authentication has a number of benefits, including better usability and higher security.

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Predicting the Time from Diagnosis to Treatment in Breast Cancer

Predicting the Time from Diagnosis to Treatment in Breast Ca...

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E-Health and Bioengineering Conference (EHB)

作者： Sergiu Ceică Ştefan-Daniel Achirei Dept. of Computer Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iasi Iasi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Recent advancements in machine learning (ML) have significantly impacted the medical field, particularly in diagnosing and treating breast cancer. This study models the time from diagnosis to treatment for breast cancer patients, focusing on delay factors and ML-based solutions. The goal is to develop precise ML models that predict treatment delays, thereby improving the quality and efficiency of medical services. We investigated socio-economic disparities affecting treatment access and developed models to predict these delays. The predictive models used include K-Nearest Neighbors, Decision Trees, Linear Regression, and Boosting Algorithms such as AdaBoost and Gradient Boosting Regressor. By accurately predicting the interval from diagnosis to the first treatment, our work aims to promote equity in healthcare, ensuring timely treatment for all patients. Our findings highlight the potential of ML in optimizing treatment timelines and resource allocation, contributing to improved patient outcomes and advancing the medical system.

关键词： Medical services Predictive models Boosting Prediction algorithms Breast cancer Delays Resource management Socioeconomics Medical diagnostic imaging Regression tree analysis

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Home Care Assistance Solution based on a Software Multi-Agents System 24

Home Care Assistance Solution based on a Software Multi-Agen...

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24th International Conference on control Systems and computer Science, CSCS 2023

作者： Rasras, Mohammad Marin, Iuliana Radu, Serban University Politehnica of Bucharest Doctoral School of Automatic Control and Computers Bucharest Romania University Politehnica of Bucharest Dept. of Engineering in Foreign Languages Bucharest Romania University Politehnica of Bucharest Dept. of Computer Science Bucharest Romania

ISBN: (纸本)9798350313390

A smart home allows automated technology to control systems and appliances to assist daily life activities. In the current work, a prototype of a designed smart home health-aware system is presented. Three predefined ruled agents have been used to gather data, communicate between themselves, interpret the data based on several machine learning algorithms to predict abnormality for cardiac conditions. The paper also compares results obtained by running five machine learning algorithms. The agents function in accordance with predefined dataset describing residents ' age, gender, height, weight, systolic and diastolic blood pressure, cholesterol, and glucose levels, smoking and alcohol consumption habits, and lastly, physical activity. Our plan is to simplify ubiquitous health monitoring for smart home's residents. The proposed solution aims to monitor parametric measurements to alert health specialists in case of emergencies. © 2023 IEEE.

关键词： Multi agent systems

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Workforce Challenges Posed by the COVID-19 Pandemic: YouTube as a Data Source

Workforce Challenges Posed by the COVID-19 Pandemic: YouTube...

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Construction Research Congress 2024, CRC 2024

作者： Jamil Uddin, S.M. Tamanna, Mahzabin Alsharef, Abdullah Ovid, Anto Albert, Alex Stock Development Dept. of Construction Management Florida Gulf Coast Univ. Fort MyersFL United States Dept. of Computer Science North Carolina State Univ. RaleighNC United States Dept. of Civil Engineering King Saud Univ. Riyadh Saudi Arabia Dept. of Civil Construction and Environmental Engineering North Carolina State Univ RaleighNC United States

ISBN: (数字)9780784485293

ISBN: (纸本)9780784485293

The COVID-19 pandemic is one of the biggest challenges the world has faced in recent decades. The pandemic has disrupted human life in significant ways. Similar to many other industries, the construction industry has faced numerous challenges due to the pandemic. Some of the challenges include project shutdowns, supply chain disruptions, health and safety challenges, project delays, and economic hardships. This study is focused on unveiling workforce-related challenges the industry experienced during the early stages of the COVID-19 pandemic. The investigation leveraged YouTube as the source of information given the presence of rich and relevant content. As a first step, YouTube's application programming interface (API) was used to extract relevant videos using appropriate keywords. The analysis of the videos revealed a number of workforce-related challenges that the pandemic posed. These included job losses, lower wages, financial stress, and fringe benefit losses. Additionally, the videos highlighted the challenges of migrant workers from different regions, including the US, Canada, Europe, Singapore, the Middle East, and others. The videos also unveiled the struggle of minority workers such as Hispanic workers in the US. The findings of this study can be utilized by industry stakeholders and governments to overcome workforce-related challenges during similar emergencies in the future. © CRC 2024. All rights reserved.

关键词： COVID-19

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A New Robust Hybrid Active Noise control System 8

A New Robust Hybrid Active Noise Control System

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8th International Conference on Signal and Image Processing, ICSIP 2023

作者： Wang, Z. Xiao, Y. Ma, Y. Ma, L. Khorasani, K. Prefectural University of Hiroshima Dept. of Management & Information Systems Hiroshima734-8558 Japan Institute of Automation Jiangnan University Wuxi214122 China Concordia University Dept. of Electrical & Computer Engineering Montreal Canada

ISBN: (纸本)9798350397932

The conventional hybrid active noise control (ANC, HANC) may significantly degrade if the reference signal for the feedforward ANC (FFANC) subcontroller consists of not only a broadband component but also a low-frequency sinusoidal component that is uncorrelated or partially correlated with the narrowband noise component that is attenuated by the feedback ANC (FBANC) subcontroller. In this paper, a new robust HANC system is proposed to mitigate the performance degradation resulting from the low-frequency sinusoidal component. A band-pass filter bank (BPFB) is applied to the FFANC reference signal to separate the low-frequency sinusoidal component from the broadband one and each of them is fed to an FFANC subcontroller that solely focuses on a single noise component. A supporting filter takes the extracted broadband component and the residual error as its input and desired signal, respectively. The same BPFB is then applied to the supporting filter error in order to separate the remaining low-frequency sinusoidal component from the narrowband component that persists in the residual error. The use of the two BPFBs and the supporting filter allows the three HANC subcontrollers to operate practically independently, each taking care of one of the pre-processed noise components which are uncorrelated with each other irrespective of the relationship between the two original noise sources. Extensive simulations are provided to demonstrate the improved effectiveness and robust capability of the proposed HANC as compared to its counterpart, even in a case that the low-frequency sinusoidal component in the FFANC reference signal is partially corrected with the primary narrowband noise component that is targeted by the FBANC. © 2023 IEEE.

关键词： Filter banks

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Real-Time Face Mask Detector 3

Real-Time Face Mask Detector

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3rd IEEE International Conference on Technology, engineering, management for Societal Impact using Marketing, Entrepreneurship and Talent, TEMSMET 2023

作者： Patel, Vishwajeet Guru Prasad, M.S. Aditya Pai, H. Kumar, A Suresh Praveen Gujjar, J. Naveen Kumar, H.N. Dept. of Computer Science and Engg. Dehradun India JAIN [Deemed-to-be University Faculty of Management Studies Bengaluru India Vidyavardhaka College of Engineering Dept. of Electronics and Communication Engg. Karnataka Mysuru India

ISBN: (纸本)9798350397819

When the COVID-19 pandemic was present we all have faced various challenges in our everyday lives. Pandemic created worldwide emergency which led to the lockdown in most of the countries resulting into disruption in world trade and movement. To reduce the covid cases WHO recommended to wear mask and maintain social distancing and then these steps became mandatory for some places, such as restaurants, hospitals, grocery stores etc., The purpose of limiting interaction with individuals as much as possible in such situations is simply defeated by having a staff personally check each person to make sure their mask is on. To avoid this dilemma, it became necessary to build a project named 'Real-time face mask detector', This reveals whether a mask-wearing individual is there. This project needed the use of some python libraries like TensorFlow, Keras, OpenCV. Using this project, we will be able to Detect mask-on faces in live video clip with accuracy of 97-98 %. © 2023 IEEE.

关键词： COVID-19

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Smart framework for enhancing security of IoT linked devices in Healthcare Systems 5

Smart framework for enhancing security of IoT linked devices...

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5th International Conference on Information management and Machine Intelligence, ICIMMI 2023

作者： Duvey, Anurag Anand Rahi, Pankaj Gowri Ganesh, N.S. Basa, Santi Swarup Dept. of Artificial Intelligence & Data Science Poornima Institute of Engineering and Technology Jaipur India Health Information Technology Management Indian Institute of Health Management Research Bangalore India Dept. of Artificial Intelligence & Data Science Saveetha Engineering College Chennai India Dept. of Computer Science Maharaja Sriram Chandra Bhanja Deo University Odisha Baripada India

ISBN: (纸本)9798400709418

The adoption of blockchain technology is widespread across diverse industries due to its rapid advancement and high level of innovation. The technology in question is widely acknowledged for its ability to adapt and be utilized in diverse domains, thereby enabling the storage of data in interconnected fields through peer-to-peer networks. Blockchain technology demonstrates high performance in the storage of transactions that have minimal digital traces, as well as in situations where there is a need for immutability and transparency. The utilization of blockchain technology can potentially offer advantages in various domains such as supply chain management, the maintenance of dynamic patient authorization for data use, and the verification of patient, provider, or supplier identification in certain situations. The main objective of this research study is to investigate the application of blockchain technology in improving the security of Internet of Things (IoT) systems, particularly in the context of remote patient monitoring and its linked EHR system. This article explores the advantages of incorporating Internet of Things (IoT) devices into the remote patient monitoring practice, as well as the practical challenges that may arise during the installation phase. The proposed concept utilizes sophisticated and effective cryptographic methodologies, particularly the Advanced Encryption Standard (AES) scheme, to guarantee dependable data transmission across networks and safeguarded storage within cloud environments. © 2023 ACM.

关键词： Smart contract

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Process-Model-Free Design of MPC via a Reference-Model-Based PI controller for the Gas Turbine 9

Process-Model-Free Design of MPC via a Reference-Model-Based...

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9th International Conference on Electrical engineering, control and Robotics, EECR 2023

作者： Shi, Gengjin Dai, Chengbo Ma, Miaomiao Li, Donghai Ding, Yanjun Tsinghua University State Key Lab of Power Systems Dept. of Energy & Power Engineering Beijing China North China Electric Power University School of Control & Computer Engineering Beijing China

ISBN: (纸本)9781665491204

Model predictive control (MPC) is a modern advanced control strategy which has great reputation because of its excellent reference tracking performance and the ability to deal with process constraints, time delay and multivariable problems. However, the gas turbine is difficult to model accurately and unmeasurable disturbances are unavoidable, which limits the application of MPC to the gas turbine. To solve these problems, a process-model-free design method for MPC via a reference-model (RM)-based proportional-integral (PI) controller-desired dynamic equational (DDE)-PI controller (MPC-DDE) is proposed in this paper. The DDE-PI provides the design model for the MPC and handle with unmeasurable disturbances while MPC provides a rolling optimized set point for DDE-PI. Simulation results illustrate the superiorities of the proposed hierarchical control strategy in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of practical application of MPC-DDE to the gas turbine. © 2023 IEEE.

关键词： Model predictive control

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Modified feedback narrowband active noise control with online secondary-path modeling 24

Modified feedback narrowband active noise control with onlin...

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24th International Congress on Acoustics, ICA 2022

作者： Ma, Yaping Xiao, Yegui Ma, Liying Khorasani, Khashayar Dept. of Automation Jiangnan University China Dept. of Information and Management System Prefectural University of Hiroshima Japan Dept. of Electrical and Computer Engineering Concordia University Canada

Feedback narrowband active noise control (NANC, FBNANC) systems have been developed to suppress sinusoidal noise signals generated by rotating machines such as diesel engines, fans, etc. They do not require any reference sensor and can avoid the frequency mismatch and the acoustic feedback, as compared with the conventional feedforward NANC (FFNANC) systems. In this paper, a modified FBNANC system is proposed which contains three subsystems, namely: 1) a cascade pre-filtered and parallelly updated adaptive notch filter bank (CPANFB) that is included to synthesize the reference sinusoidal signals for the FBNANC controller, 2) an online secondary-path modeling (SPM, OSPM) subsystem that is introduced into the new system to track the secondary-path changes, and 3) a bandpass filter bank that is applied to the residual noise for separating the remaining sinusoids from other broadband noise components, with the former utilized to scale the auxiliary white Gaussian noise (AWGN) for the purpose of reducing its contribution to the residual noise. The three subsystems including the MPA (magnitude and phase adjuster) based controller are seamlessly integrated to work in harmony such that the whole FBNANC system enjoys nice advantages in both convergence and noise reduction performance (NRP). Extensive simulations are conducted to demonstrate and confirm the effectiveness of the proposed system. © ICA *** rights reserved

关键词： adaptive notch filter bank (ANFB) Feedback narrowband active noise control (FBNANC) magnitude noise reduction performance (NRP) online secondary-path modeling (OSPM) phase adjuster (MPA)

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A Digital Healthcare Service Architecture for Seniors Safety Monitoring in Metaverse

A Digital Healthcare Service Architecture for Seniors Safety...

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2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023

作者： Qu, Qian Xu, Ronghua Sun, Han Chen, Yu Sarkar, Sumantra Ray, Indrajit Binghamton University Dept. of Electrical and Computer Engineering BinghamtonNY13902 United States Binghamton University School of Management BinghamtonNY13902 United States Colorado State University Dept. of Computer Science Fort CollinsCO80523 United States

ISBN: (纸本)9798350333336

We have been witnessing an unprecedented increase in the aging population in human history. It is nontrivial to ensure the health and safety of seniors living alone. The prohibitive human labor cost necessitates more sustainable, technology-oriented approaches instead of labor-intensive solutions. The raising digital healthcare services (DHS) leveraging the Internet of Medical Things (IoMT), Digital Twins (DT), and advanced fifth-generation and beyond (B5G) wireless communication technology, are widely recognized as promising solutions. By enabling a seamless interwoven of the physical world and cyberspace, Metaverse makes an ideal home for the next generation of DHS. Thanks to characteristics of decentralization, traceability, and unalterability, Blockchain is envisioned to enhance security properties in Metaverse. This paper proposes MetaSafe, a DHS architecture for seniors' safety monitoring in Metaverse. Based on monitoring data collected by sensors, the activities and status of seniors, who are considered as the physical objects (PO), are mirrored to corresponding logical objects (LO) in a virtual community in the Metaverse, where activity recognition, potential risk prediction, and alert generation are realized. By leveraging Non-Fungible Token (NFT) technology to tokenize identities (POs and LOs) and data streams of the DHS on the blockchain, an NFT-based authentication fabric allows for verifiable ownership and traceable transferability during the data-sharing process. Specifically, an instant alerting system is introduced in this work that leverages a hybrid algorithm combining the singular spectrum analysis (SSA) approach with the long-short-term memory (LSTM) networks. Through an extensive experimental study, MetaSafe is validated as a feasible and promising approach to protect seniors living alone. © 2023 IEEE.

关键词： Blockchain

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