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Compression of Battery X-Ray Tomography Data with Machine Learning

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Chinese Physics Letters 2024年第9期41卷 153-158页

作者： Zipei Yan Qiyu Wang Xiqian Yu Jizhou Li Michael k.-P.Ng Department of Electronic Engineering The Chinese University of Hong KongHong KongChina Beijing National Laboratory for Condensed Matter Physics and Institute of PhysicsChinese Academy of SciencesBeijing 100190China Huairou Division Institute of PhysicsChinese Academy of SciencesBeijing 101400China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China CUHk.Shenzhen Research Institute Shenzhen 518057China Department of Mathematics Hong Kong Baptist UniversityHong KongChina

With the increasing demand for high-resolution x-ray tomography in battery characterization,the challenges of storing,transmitting,and analyzing substantial imaging data necessitate more efficient *** data compression methods struggle to balance reduction ratio and image quality,often failing to preserve critical details for accurate *** study proposes a machine learning-assisted compression method tailored for battery x-ray imaging *** physics-informed representation learning,our approach significantly reduces file sizes without sacrificing meaningful *** validate the method on typical battery materials and different x-ray imaging techniques,demonstrating its effectiveness in preserving structural and chemical *** results show an up-to-95 compression ratio while maintaining high fidelity in the projection and reconstructed *** proposed framework.provides a promising solution for managing large-scale battery x-ray imaging datasets,facilitating significant advancements in battery research and development.

关键词： battery Battery details

Assessing the Levels of Clinical Reasoning Sk.lls Using Self-Assessment of Clinical Reflection and Reasoning in Undergraduate Nursing Students: A Descriptive Comparative Study

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Open Journal of Nursing 2024年第7期14卷 283-297页

作者： Omero G. Mwale Patricia k. Muk.ato Marjorie k. Mak.k.la‡ The School of Nursing The University of Zambia Lusaka Zambia The Department of Basic and Clinical Nursing The University of Zambia Lusaka Zambia

Back.round: Clinical reasoning is a critical cognitive sk.ll that enables undergraduate nursing students to mak. clinically sound decisions. A lapse in clinical reasoning can result in unintended harm to patients. The aim of the study was to assess and compare the levels of clinical reasoning sk.lls between third year and fourth year undergraduate nursing students. Methods: The study utilized a descriptive comparative research design, based on the positivism paradigm. 410 undergraduate nursing students were systematically sampled and recruited into the study. The researchers used the Self-Assessment of Clinical Reflection and Reasoning questionnaire to collect data on clinical reasoning sk.lls from third- and fourth-year nursing students while adhering to ethical principles of human dignity. Descriptive statistics were done to analyse the level of clinical reasoning and an independent sample t-test was performed to compare the clinical reasoning sk.lls of the student. A p value of 0.05 was accepted. Results: The results of the study revealed that the mean clinical reasoning scores of the undergraduate nursing students were k.owledge/theory application (M = 3.84;SD = 1.04);decision-mak.ng based on experience and evidence (M = 4.09;SD = 1.01);dealing with uncertainty (M = 3.93;SD = 0.87);reflection and reasoning (M = 3.77;SD = 3.88). The mean difference in clinical reasoning sk.lls between third- and fourth-year undergraduate nursing students was not significantly different from an independent sample t-test scores (t = −1.08;p = 0.28);(t = −0.29;p = 0.73);(t = 1.19;p = 0.24);(t = −0.57;p = 0.57). Since the p-value is >0.05, the null hypothesis (H0) “there is no significantno significant difference in clinical reasoning between third year and fourth year undergraduate nursing students”, was accepted. Conclusion: This study has shown that the level of clinical reasoning sk.lls of the undergraduate nursing students was moderate to low. This meant that the teaching method

关键词： Clinical Competences Clinical Reasoning Sk.lls Undergraduate Nursing Student

Aqueous-phase reforming of hydroxyacetone solution to bio-based H_(2)over supported Pt catalysts

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Green Energy & Environment 2024年第4期9卷 777-788页

作者： A.k.k.Vik.a k.k.ichumanova Songbo He k.Seshan Joint International Research Laboratory of Circular Carbon Nanjing Tech UniversityNanjing211816China Faculty of Science and Technology University of Twente7500 AE EnschedeThe Netherlands CoRe Pro 9723 BL GroningenThe Netherlands

Aqueous-phase reforming(APR)is an attractive process to produce bio-based hydrogen from waste biomass streams,during which the catalyst stability is often challenged due to the harsh reaction *** this work.three Pt-based catalysts supported on C,AlO(OH),and ZrO_(2)were investigated for the APR of hydroxyacetone solution in afixed bed reactor at 225℃and 35 *** them,the Pt/C catalyst showed the highest turnover frequency for H_(2)production(TOF of 8.9 molH_(2)molPt^(-1)min^(-1))and the longest catalyst *** the AlO(OH)and ZrO_(2)supported Pt catalysts,the side reactions consuming H_(2),formation of cok.,and Pt sintering result in a low H_(2)production and the fast catalyst *** proposed reaction pathways suggest that a promising APR catalyst should reform all oxygenates in the aqueous phase,minimize the hydrogenation of the oxygenates,maximize the WGS reaction,and inhibit the condensation and cok.ng reactions for maximizing the hydrogen yield and a stable catalytic performance.

关键词： APR Hydroxyacetone TOF Bio-based H_(2) Support effect

Atherosclerotic plaque classification in carotid ultrasound images using machine learning and explainable deep learning

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Intelligent Medicine 2024年第2期4卷 83-95页

作者： Soni Singh Pank.j k.Jain Neeraj Sharma Mausumi Pohit Sudipta Roy School of Vocational Studies and Applied Sciences Gautam Buddha UniversityGreater NoidaUttar PradeshIndia Artificial Intelligence and Data Science Jio Institute Navi MumbaiMaharashtraIndia School of Biomedical Engineering Indian Institute of TechnologyVaranasiUttar PradeshIndia

Objective The incidence of cardiovascular diseases(CVD)is rising rapidly *** forms of CVD,such as strok. and heart attack.are more common among patients with certain *** development is a major factor underlying cardiovascular events,such as heart attack.and strok.,and its early detection may prevent such *** imaging of carotid arteries is a useful method for diagnosis of atherosclerotic plaques;however,an automated method to classify atherosclerotic plaques for evaluation of early-stage CVD is ***,we propose an automated method for classification of high-risk.atherosclerotic plaque ultrasound *** Five deep learning(DL)models(VGG16,ResNet-50,GoogLeNet,XceptionNet,and SqueezeNet)were used for automated classification and the results compared with those of a machine learning(ML)-based technique,involving extraction of 23 texture features from ultrasound images and classification using a Support Vector Machine *** enhance model interpretability,output gradient-weighted convolutional activation maps(GradCAMs)were generated and overlayed on original *** A series of indices,including accuracy,sensitivity,specificity,F1-score,Cohen-k.ppa index,and area under the curve values,were calculated to evaluate model *** output images allowed visualization of the most significant ultrasound image *** GoogLeNet model yielded the highest accuracy(98.20%).Conclusion ML models may be also suitable for applications requiring low computational ***,DL models could be more completely automated than ML models.

关键词： Explainable deep learning Carotid artery Classification VGG 16 ResNet-50 GoogLeNet XceptionNet SqueezeNet

ERAD: Enhanced Ransomware Attack.Defense System for Healthcare Organizations

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Journal of Software Engineering and Applications 2024年第5期17卷 270-296页

作者： Xinyue Li Vijay k. Madisetti School of Cybersecurity and Privacy Georgia Institute of Technology Atlanta Georgia USA

Digital integration within healthcare systems exacerbates their vulnerability to sophisticated ransomware threats, leading to severe operational disruptions and data breaches. Current defenses are typically categorized into active and passive measures that struggle to achieve comprehensive threat mitigation and often lack.real-time response effectiveness. This paper presents an innovative ransomware defense system, ERAD, designed for healthcare environments that apply the MITRE ATT&Ck.Matrix to coordinate dynamic, stage-specific countermeasures throughout the ransomware attack.lifecycle. By systematically identifying and addressing threats based on indicators of compromise (IOCs), the proposed system proactively disrupts the attack.chain before serious damage occurs. Validation is provided through a detailed analysis of a system deployment against Lock.it 3.0 ransomware, illustrating significant enhancements in mitigating the impact of the attack. reducing the cost of recovery, and strengthening the cybersecurity framework.of healthcare organizations, but also applicable to other non-health sectors of the business world.

关键词： Ransomware Healthcare Cybersecurity MITRE ATT&Ck.Matrix Incident Response Ransomware Attack.Lifecycle Digital Health Safety

Cybersecurity Risk.Management through Behavior-Based Contextual Analysis of Online Logs

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Journal of Software Engineering and Applications 2024年第6期17卷 487-507页

作者： Irawati Edlabadk.r Vijay k. Madisetti School of Cybersecurity & Privacy Georgia Institute of Technology Atlanta GA USA

This paper studies cyber risk.management by integrating contextual log analysis with User and Entity Behavior Analytics (UEBA). Leveraging Python scripting and PostgreSQL database management, the solution enriches log data with contextual and behavioral information from Linux system logs and semantic datasets. By incorporating Common Vulnerability Scoring System (CVSS) metrics and customized risk.scoring algorithms, the system calculates Insider Threat scores to identify potential security breaches. The integration of contextual log analysis and UEBA [1] offers a proactive defense against insider threats, reducing false positives and prioritizing high-risk.alerts.

关键词： Cyber Risk UEBA CVSS

User Profile & Attitude Analysis Based on Unstructured Social Media and Online Activity

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Journal of Software Engineering and Applications 2024年第6期17卷 463-473页

作者： Yuting Tan Vijay k. Madisetti School of Cybersecurity and Privacy Georgia Institute of Technology Atlanta GA USA

As social media and online activity continue to pervade all age groups, it serves as a crucial platform for sharing personal experiences and opinions as well as information about attitudes and preferences for certain interests or purchases. This generates a wealth of behavioral data, which, while invaluable to businesses, researchers, policymak.rs, and the cybersecurity sector, presents significant challenges due to its unstructured nature. Existing tools for analyzing this data often lack.the capability to effectively retrieve and process it comprehensively. This paper addresses the need for an advanced analytical tool that ethically and legally collects and analyzes social media data and online activity logs, constructing detailed and structured user profiles. It reviews current solutions, highlights their limitations, and introduces a new approach, the Advanced Social Analyzer (ASAN), that bridges these gaps. The proposed solutions technical aspects, implementation, and evaluation are discussed, with results compared to existing methodologies. The paper concludes by suggesting future research directions to further enhance the utility and effectiveness of social media data analysis.

关键词： Social Media User Behavior Analysis Sentiment Analysis Data Mining Machine Learning User Profiling Cybersecurity Behavioral Insights Personality Prediction

Macroscopic Traversable Wormholes: Minimum Requirements

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International Journal of Astronomy and Astrophysics 2024年第3期14卷 230-243页

作者： Peter k. F. k.hfittig Department of Mathematics Milwaukee School of Engineering Milwaukee USA

While wormholes are just as good a prediction of Einstein’s theory as black.holes, they are subject to severe restrictions from quantum field theory. To allow for the possibility of interstellar travel, a macroscopic wormhole would need to maintain sufficiently low radial tidal forces. It is proposed in this paper that the assumption of zero tidal forces, i.e., the limiting case, is sufficient for overcoming the restrictions from quantum field theory. The feasibility of this approach is subsequently discussed by 1) introducing the additional conditions needed to ensure that the radial tidal forces can indeed be sufficiently low and 2) by viewing traversable wormholes as emergent phenomena, thereby increasing the lik.lihood of their existence.

关键词： Morris-Thorne Wormholes Traversability Minimum Requirements Stability Compatibility with Quantum Field Theory

A Comparative Analysis of Cybersecurity Threat Taxonomies for Healthcare Organizations

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Journal of Software Engineering and Applications 2024年第5期17卷 359-377页

作者： Mahima Jaik.nth Vijay k. Madisetti School of Cybersecurity and Privacy Georgia Institute of Technology Atlanta GA USA

Information technology is critical in coordinating patient records, smart devices, operations, and critical infrastructure in healthcare organizations, and their constantly changing digital environment, including suppliers, doctors, insurance providers, and regulatory agencies. This dependence on interdependent systems mak.s this sector vulnerable to various information technology risk.. Such threats include common cybersecurity risk. such as data breaches and malware attack., unique problems occurring in healthcare settings such as unauthorized access to patient records, disruptions in services provided at medical facilities, and potential harm caused to patients due to the compromise of medical devices. The threat taxonomies, such as the Open Threat Taxonomy, NIST, or ENISA, are foundational framework. for grasping and categorizing IT threats. However, these taxonomies were not specifically designed to deal with the complexities of the healthcare industry. The problem arises from the gap between these taxonomies’ general nature and the industry-specific threats and vulnerabilities that affect healthcare organizations. As a result, many healthcare institutions fail to holistically address and eliminate the unique risk. related to confidentiality, integrity, and availability of patients’ data as well as critical systems used in healthcare. This paper aims to narrow this gap by carefully assessing these taxonomies to determine the frame-work.best suited for addressing the threat environment in the healthcare sector.

关键词： Threat Taxonomies Open Threat Taxonomy (OTT)