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Integrated Machine Learning and Deep Learning Models for Cardiovascular Disease Risk Prediction: A Comprehensive Comparative Study

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Journal of Intelligent Learning Systems and Applications 2024年第1期16卷 12-22页

作者： Shadman Mahmood Khan Pathan Sakan Binte Imran Departmentof Electrical and Computer Engineering Old Dominion University Norfolk USA Sir Salimullah Medical College Dhaka Bangladesh

Cardiovascular Diseases (CVDs) pose a significant global health challenge, necessitating accurate risk prediction for effective preventive measures. This comprehensive comparative study explores the performance of traditional Machine Learning (ML) and Deep Learning (DL) models in predicting CVD risk, utilizing a meticulously curated dataset derived from health records. Rigorous preprocessing, including normalization and outlier removal, enhances model robustness. Diverse ML models (Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbor, Decision Tree, and Gradient Boosting) are compared with a Long Short-Term Memory (LSTM) neural network for DL. Evaluation metrics include accuracy, ROC AUC, computation time, and memory usage. Results identify the Gradient Boosting Classifier and LSTM as top performers, demonstrating high accuracy and ROC AUC scores. Comparative analyses highlight model strengths and limitations, contributing valuable insights for optimizing predictive strategies. This study advances predictive analytics for cardiovascular health, with implications for personalized medicine. The findings underscore the versatility of intelligent systems in addressing health challenges, emphasizing the broader applications of ML and DL in disease identification beyond cardiovascular health.

关键词： Cardiovascular Disease Machine Learning Deep Learning Predictive Modeling Risk Assessment Comparative Analysis Gradient Boosting LSTM

Ultrafast magneto-optical dynamics in nickel(111)single crystal studied by the integration of ultrafast reflectivity and polarimetry probes

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Chinese Physics B 2024年第3期33卷 65-69页

作者：匡皓余军潇陈洁 H.E.Elsayed-Ali 李润泽 Peter M.Rentzepis School of Physical Science and Technology ShanghaiTech UniversityShanghai 201210China Center for Transformative Science ShanghaiTech UniversityShanghai 201210China Center for Ultrafast Science and Technology Key Laboratory for Laser Plasmas (Ministry of Education)Collaborative Innovation Center of IFSA (CICIFSA)School of Physics and AstronomyShanghai Jiao Tong UniversityShanghai 200240China Department of Electrical and Computer Engineering Old Dominion UniversityNorfolkVirginia 23529USA Department of Electrical and Computer Engineering Texas A&M UniversityCollege StationTexas 77843USA

With the integration of ultrafast reflectivity and polarimetry probes,we observed carrier relaxation and spin dynamics induced by ultrafast laser excitation of Ni(111)single crystals.The carrier relaxation time within the linear excitation range reveals that electron-phonon coupling and dissipation of photon energy into the bulk of the crystal take tens of picoseconds.On the other hand,the observed spin dynamics indicate a longer time of about 120 ps.To further understand how the lattice degree of freedom is coupled with these dynamics may require the integration of an ultrafast diffraction probe.

关键词： ultrafast spin dynamics non-equilibrium dynamics multi-probe

DeepPOSE:Detecting GPS spoofing attack via deep recurrent neural network

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Digital Communications and Networks 2022年第5期8卷 791-803页

作者： Peng Jiang Hongyi Wu Chunsheng Xin ECE Dept.and School of Cybersecurity Old Dominion UniversityNorfolkVA23529USA

The Global Positioning System(GPS)has become a foundation for most location-based services and navigation systems,such as autonomous vehicles,drones,ships,and wearable devices.However,it is a challenge to verify if the reported geographic locations are valid due to various GPS spoofing tools.Pervasive tools,such as Fake GPS,Lockito,and software-defined radio,enable ordinary users to hijack and report fake GPS coordinates and cheat the monitoring server without being detected.Furthermore,it is also a challenge to get accurate sensor readings on mobile devices because of the high noise level introduced by commercial motion sensors.To this end,we propose DeepPOSE,a deep learning model,to address the noise introduced in sensor readings and detect GPS spoofing attacks on mobile platforms.Our design uses a convolutional and recurrent neural network to reduce the noise,to recover a vehicle's real-time trajectory from multiple sensor inputs.We further propose a novel scheme to map the constructed trajectory from sensor readings onto the Google map,to smartly eliminate the accumulation of errors on the trajectory estimation.The reconstructed trajectory from sensors is then used to detect the GPS spoofing attack.Compared with the existing method,the proposed approach demonstrates a significantly higher degree of accuracy for detecting GPS spoofing attacks.

关键词： GPS spoofing attack Position estimation Recurrent neural network

A channel state information based virtual MAC spoofing detector

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High-Confidence Computing

High-Confidence Computing 2022年第3期2卷 1-6页

作者： Peng Jiang Hongyi Wu Chunsheng Xin Department of ECE Old Dominion UniversityNorfolkVAUSA School of Cybersecurity Old Dominion UniversityNorfolkVAUSA

Physical layer security has attracted lots of attention with the expansion of wireless devices to the edge networks in recent years.Due to limited authentication mechanisms,MAC spoofing attack,also known as the identity attack,threatens wireless systems.In this paper,we study a new type of MAC spoofing attack,the virtual MAC spoofing attack,in a tight environment with strong spatial similarities,which can create multiple counterfeits entities powered by the virtualization technologies to interrupt regular services.We develop a system to effectively detect such virtual MAC spoofing attacks via the deep learning method as a countermeasure.A deep convolutional neural network is constructed to analyze signal level information extracted from Channel State Information(CSI)between the communication peers to provide additional authentication protection at the physical layer.A significant merit of the proposed detection system is that this system can distinguish two different devices even at the same location,which was not well addressed by the existing approaches.Our extensive experimental results demonstrate the effectiveness of the system with an average detection accuracy of 95%,even when devices are co-located.

关键词： Virtual Mac spoofing Channel state information Deep learning

Short range correlations in nuclei

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Chinese Physics C 2010年第9期34卷 1224-1228页

作者： L.B.Weinstein Physics Department Old Dominion University

Studying nucleon-nucleon （NN） correlated pairs will teach us a great deal about the high momentum part of the nuclear wave function,the short range part of the NN interaction,and the nature of cold dense nuclear matter.These correlations are similar in all nuclei,differing only in magnitude.High momentum nucleons,p 〉p fermi,all have a correlated partner with approximately equal and opposite momentum.At pair relative momenta of 300 〈prel 〈500 MeV/c,these correlated pairs are dominated by tensor correlations.This is shown by the dominance of pn over pp pairs at pair total momentum and by the parity of pn to pp pairs at large pair total momentum.

关键词： correlations nucleon momentum distributions tensor correlations

On the chronological understanding of the homogeneous dielectric barrier discharge

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High Voltage 2023年第6期8卷 1132-1150页

作者： Xinpei Lu Zhi Fang Dong Dai Tao Shao Feng Liu Cheng Zhang Dawei Liu Lanlan Nie Chunqi Jiang State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhanChina College of Electrical Engineering and Control Science Nanjing Tech TechnologyNanjingChina School of Electric Power South China University of TechnologyGuangzhouChina Institute of Electrical Engineering Chinese Academy of SciencesBeijingChina Frank Reidy Research Center for Bioelectrics Old Dominion UniversityNorfolkVirginiaUSA Department of Electrical and Computer Engineering Old Dominion UniversityNorfolkVirginiaUSA

Dielectric barrier discharges(DBD)are widely utilised non‐equilibrium atmospheric pressure plasmas with a diverse range of applications,such as material processing,surface treatment,light sources,pollution control,and medicine.Over the course of several decades,extensive research has been dedicated to the generation of homogeneous DBD(H‐DBD),focussing on understanding the transition from H‐DBD to filamentary DBD and exploring strategies to create and sustain H‐DBD.This paper first discusses the in-fluence of various parameters on DBD,including gas flow,dielectric material,surface conductivity,and mesh electrode.Secondly,a chronological literature review is presented,highlighting the development of H‐DBD and the associated understanding of its un-derlying mechanisms.This encompasses the generation of H‐DBD in helium,nitrogen,and air.Lastly,the paper provides a brief overview of multiple‐current‐pulse(MCP)behaviours in H‐DBD.The objective of this article is to provide a chronological un-derstanding of homogeneous dielectric barrier discharge(DBD).This understanding will aid in the design of new experiments aimed at better comprehending the mechanisms behind H‐DBD generation and ultimately assist in achieving large‐volume H‐DBD in an air environment.

关键词： dielectric barrier pollution

Sustainable growth research–A study on the telecom operators in China

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Journal of Management Analytics 2022年第1期9卷 17-31页

作者： Hong Chena Ling Li Yong Chen School of Business and Economics Indiana University EastRichmondINUSA College of Business and Public Administration Old Dominion UniversityNorfolkVAUSA Department of Management Information Systems and Data Analytics Texas A&M International UniversityLaredoTXUSA

In recent years,the telecom industry has faced digital transformation challenges and fierce market competition.The challenges push telecom operators to grow their subscriber bases by offering lower prices and improved services and new features,which puts pressure on operators’profitability.In addition,the rise of Internet companies gradually erodes the profit of the traditional telecom operators.Therefore,paying attention to the critical factors impacting firm sustainable growth can help operators get out of the predicament.Based on the resource-based view(RBV),this study explores the factors that influence the firm sustainable growth.Multiple regression model is applied to empirically test the hypotheses with longitudinal time-series panel data from major telecom operators in China.The study provides empirical evidence for sustainable growth research and useful insights for practitioners on the way to keep sustainable growth.

关键词： Sustainable growth telecom operator multiple regression model

A goal-based approach to the identification of essential transformation variables in support of the implementation of the 2030 agenda for sustainable development

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International Journal of Digital Earth 2020年第2期13卷 166-187页

作者： Hans-Peter Plag Shelley-Ann Jules-Plag Department of Ocean Earth and Atmospheric SciencesOld Dominion UniversityNorfolkVAUSA Mitigation and Adaptation Research Institute Old Dominion UniversityNorfolkVAUSA Tiwah UG RossbachGermany Department of Engineering Management and Systems EngineeringOld Dominion UniversityNorfolkVAUSA

The United Nations’2030 Agenda for Sustainable Development sets seventeen Sustainable Development Goals(SDGs)to be achieved by 2030.Earth observation are needed that can support the development and validation of transformation policies to make progress towards the SDGs.A participatory and inclusive goal-based approach(GBA)is introduced that links societal goals,targets and indicators to Essential Transformation Variables(ETVs)of the human and non-human environment.The GBA is complementary to the widely used expertbased approach.The GBA is applied to the SDGs at the goal,target and indicator levels.The high-level conceptual model used for the SDGs is humanity embedded in the Earth’s life-support system(ELSS).At the goal level,very few of the SDGs are directly focusing on the ELSS and its physiology.Most of the SDG Targets focus on transformations in society and the built environment.Having targets that explicitly focus on the physiology of the ELSS would be important for sustainability.Most of the current indicator measure the built environment and the embedded social fabric.Sustainable development requires a functioning ELSS,and to ensure this,complementary indicators that bring environmental aspects to the monitoring of SDG targets are needed.

关键词： 2030 agenda for sustainable development sustainable development goals targets indicators essential variables policy making decision making tranformation science

The Space Infrastructure Vulnerability Cadastre:Orbital Debris Critical Loads

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International Journal of Disaster Risk Science 2015年第4期6卷 359-371页

作者： Adrian V.Gheorghe Daniel E.Yuchnovicz Department of Engineering Management and Systems Engineering Old Dominion University

Orbital debris from over 50 years of human activity in space are threatening the operations of existing and future satellites and the sustainability of high-value satellite orbits. This technical memorandum calls for the development of a cadastre that depicts the vulnerability of critical satellite orbits to accumulating orbital debris. A space infrastructure vulnerability cadastre could serve as a governance tool for use by developers and operators of critical space infrastructures to better communicate the current and future vulnerability of high-value orbits to the accumulation of orbital debris. These high-value orbits are susceptible to 'loss' for decades or centuries if generation of orbital debris continues unabated. The concept of environmental critical loads is applied to heavily used orbits as a way to indicate acceptable debris density for satellite operations, and when debris density/risk thresholds approach unacceptable levels that reduce the probability of sustaining spacecraft operations in those orbits.

关键词：轨道的碎片卫星轨道空间地籍图空间基础结构