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A Bayesian multi-model inference methodology for imprecise momentindependent global sensitivity analysis of rock structures

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第3期16卷 840-859页

作者： Akshay Kumar gaurav Tiwari Department of Civil Engineering Indian Institute of Technology(IIT)KanpurKanpur208016India

Traditional global sensitivity analysis(GSA)neglects the epistemic uncertainties associated with the probabilistic characteristics(*** of distribution type and its parameters)of input rock properties emanating due to the small size of datasets while mapping the relative importance of properties to the model *** paper proposes an augmented Bayesian multi-model inference(BMMI)coupled with GSA methodology(BMMI-GSA)to address this issue by estimating the imprecision in the momentindependent sensitivity indices of rock structures arising from the small size of input *** methodology employs BMMI to quantify the epistemic uncertainties associated with model type and parameters of input *** estimated uncertainties are propagated in estimating imprecision in moment-independent Borgonovo’s indices by employing a reweighting approach on candidate probabilistic *** proposed methodology is showcased for a rock slope prone to stress-controlled failure in the Himalayan region of *** proposed methodology was superior to the conventional GSA(neglects all epistemic uncertainties)and Bayesian coupled GSA(B-GSA)(neglects model uncertainty)due to its capability to incorporate the uncertainties in both model type and parameters of *** Borgonovo’s indices estimated via proposed methodology provide the confidence intervals of the sensitivity indices instead of their fixed-point estimates,which makes the user more informed in the data collection *** performed with the varying sample sizes suggested that the uncertainties in sensitivity indices reduce significantly with the increasing sample *** accurate importance ranking of properties was only possible via samples of large ***,the impact of the prior knowledge in terms of prior ranges and distributions was significant;hence,any related assumption should be made carefully.

关键词： Bayesian inference Multi-model inference Statistical uncertainty Global sensitivity analysis(GSA) Borgonovo’s indices Limited data

Airway management training program for nurses via online course in COVID-19 preparedness

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World Journal of Methodology 2022年第3期12卷 113-121页

作者： Bhavna Gupta gaurav jain Sharmishtha Pathak Priyanka Mishra Hemanth Kumar Shalinee Rao Department of Anesthesia All India Institute of Medical Sciences Rishikesh 249203 Uttarakhand India. Department of Anesthesia All India Institute of Medical Sciences Rishikesh 249203 Uttarakhand India. pmishra15390@***. Department of Advanced Centre of Continuous Professional Development All India Institute of Medical Sciences Rishikesh 249203 Uttarakhand India.

BACKGROUND Nursing officers are an integral component of any medical *** participate in taking care of basic airway management and assist in advanced airway management,specifically amidst the current coronavirus disease 2019(COVID-19)*** To assess the efficacy of a standardized web-based training module for nurses in preparedness to fight against *** The training was held in three sessions of 1 h each,consisting of live audio-visual lectures,case scenarios,and skill *** sequence of airway equipment,drug preparation,airway examination,and plans of airway management was demonstrated through mannequin-based *** Pre-and post-test scores as well as objective structured clinical examination scores were analyzed using Student’s t-test and the Likert scale was used for feedback *** was found that the mean score out of the total score of 20 was 8.47±4.2 in the pre-test,while in the post-test it was 17.4±1.8(P value<0.001).The participants also felt self-reliant in executing the roles of airway assistant(63.3%)and drug assistant(74.3%).Fear of self-infection with COVID-19 was also high,as 66%of participants feared working with the patient’s *** Amidst this COVID-19 emergency,when the health care systems are being persistently challenged,training of nursing staff in the safe conduct of airway management can ensure delivery of life-saving treatment.

关键词： COVID-19 Nursing Airway management Online Training Preparedness

Refinement modeling and verification of secure operating systems for communication in digital twins

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Digital Communications and Networks 2024年第2期10卷 304-314页

作者： Zhenjiang Qian Gaofei Sun Xiaoshuang Xing gaurav Dhiman School of Computer Science and Engineering Changshu Institute of TechnologySuzhou215500China University Centre for Research and Development Department of Computer Science and EngineeringChandigarh UniversityMohali140413India Department of Computer Science and Engineering Graphic Era Deemed to be UniversityDehradun248002India

In traditional digital twin communication system testing,we can apply test cases as completely as possible in order to ensure the correctness of the system implementation,and even then,there is no guarantee that the digital twin communication system implementation is completely *** verification is currently recognized as a method to ensure the correctness of software system for communication in digital twins because it uses rigorous mathematical methods to verify the correctness of systems for communication in digital twins and can effectively help system designers determine whether the system is designed and implemented *** this paper,we use the interactive theorem proving tool Isabelle/HOL to construct the formal model of the X86 architecture,and to model the related assembly *** verification result shows that the system states obtained after the operations of relevant assembly instructions is consistent with the expected states,indicating that the system meets the design expectations.

关键词： Theorem proving Isabelle/HOL Formal verification System modeling Correctness verification

A Review of Lightweight Security and Privacy for Resource-Constrained IoT Devices

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Computers, Materials & Continua 2024年第1期78卷 31-63页

作者： Sunil Kumar Dilip Kumar Ramraj Dangi gaurav Choudhary Nicola Dragoni Ilsun You Department of Computer Science and Engineering National Institute of Technology JamshedpurJamshedpurIndia School of Computing Science and Engineering VIT University BhopalBhopal466114India Center for Industrial Software The Maersk Mc-Kinney Moller InstituteUniversity of Southern DenmarkSonderborgOdenseDenmark Department of Applied Mathematics and Computer Science Technical University of DenmarkLyngby2800Denmark Department of Information Security Cryptologyand MathematicsKookmin UniversitySeoulSouth Korea

The widespread and growing interest in the Internet of Things(IoT)may be attributed to its usefulness in many different *** settings are probed for data,which is then transferred via linked *** are several hurdles to overcome when putting IoT into practice,from managing server infrastructure to coordinating the use of tiny *** it comes to deploying IoT,everyone agrees that security is the biggest *** is due to the fact that a large number of IoT devices exist in the physicalworld and thatmany of themhave constrained resources such as electricity,memory,processing power,and square *** research intends to analyse resource-constrained IoT devices,including RFID tags,sensors,and smart cards,and the issues involved with protecting them in such restricted *** lightweight cryptography,the information sent between these gadgets may be *** order to provide a holistic picture,this research evaluates and contrasts well-known algorithms based on their implementation cost,hardware/software efficiency,and attack resistance *** also emphasised how essential lightweight encryption is for striking a good cost-to-performance-to-security ratio.

关键词： IoT a sensor device lightweight cryptography block cipher smart card security and privacy

Identification of earthquake induced structural damage based on synchroextracting transform

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Earthquake Engineering and Engineering Vibration 2024年第2期23卷 475-487页

作者： Roshan Kumar gaurav Kumar Wei Zhao Arvind R Yadav Gang Yu Jayendra Kumar Evans Amponsah Department of Electronic and Information Technology Miami College of Henan UniversityHenan 475004China Alliance University Alliance College of Engineering and DesignBanglore 562106India Department of Electronics and Comm Parul UniversityVadodra 391760India School of Electrical Engineering University of JinanJinan 250022China Department of Electronics and Comm NIT JamshedpurJamshedpur 831014India Department of Civil engineering Kwame Nkrumah University of Science and TechnologyKumasi 10959Ghana

Several popular time-frequency techniques,including the Wigner-Ville distribution,smoothed pseudo-Wigner-Ville distribution,wavelet transform,synchrosqueezing transform,Hilbert-Huang transform,and Gabor-Wigner transform,are investigated to determine how well they can identify damage to *** this work,a synchroextracting transform(SET)based on the short-time Fourier transform is proposed for estimating post-earthquake structural *** performance of SET for artificially generated signals and actual earthquake signals is examined with existing *** other tested techniques,SET improves frequency resolution to a great extent by lowering the influence of smearing along the time-frequency ***,interpretation and readability with the proposed method are improved,and small changes in the time-varying frequency characteristics of the damaged buildings are easily detected through the SET method.

关键词： cross-term damage detection earthquake signal synchroextracting transform time-frequency

An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2029-2059页

作者： Sheetal Sharma Kamali Gupta DeepaliGupta Shalli Rani gaurav Dhiman Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjab140401India PG Department of Information Technology Goswami Ganesh Dutta Sanatan Dharma CollegeChandigarh160030India Department of Computer Science Government Bikram College of CommercePatialaIndia Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon University Centre for Research and Development Department of Computer Science and EngineeringChandigarh UniversityMohali140413India Department of Computer Science and Engineering Graphic Era Deemed to be UniversityDehradun248002India Division of Research and Development Lovely Professional UniversityPunjab144001India

The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart *** address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed *** analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.

关键词： Error fault detection techniques sensor faults outliers Internet of Things

Study on sex differences and potential clinical value of threedimensional computerized tomography pelvimetry in rectal cancer patients

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World Journal of Gastrointestinal Oncology 2024年第3期16卷 773-786页

作者： Xiao-Cong Zhou Fei-Yue Ke gaurav Dhamija Hao Chen Qiang Wang Department of Colorectal Surgery The Dingli Clinical Institute of Wenzhou Medical University(Wenzhou Central Hospital)Wenzhou 325000Zhejiang ProvinceChina Postgraduate Training Base Alliance of Wenzhou Medical University Wenzhou Central HospitalWenzhou 325000Zhejiang ProvinceChina School of International Studies Wenzhou Medical UniversityWenzhou 325000Zhejiang ProvinceChina Department of Radiology The Dingli Clinical Institute of Wenzhou Medical University(Wenzhou Central Hospital)Wenzhou 325000Zhejiang ProvinceChina

BACKGROUND Laparoscopic rectal cancer radical surgery is a complex procedure affected by various ***,the existing literature lacks standardized parameters for the pelvic region and soft tissues,which hampers the establishment of consistent *** To comprehensively assess 16 pelvic and 7 soft tissue parameters through computerized tomography(CT)-based three-dimensional(3D)reconstruction,providing a strong theoretical basis to address challenges in laparoscopic rectal cancer radical *** We analyzed data from 218 patients who underwent radical laparoscopic surgery for rectal cancer,and utilized CT data for 3D pelvic *** anatomical points were carefully marked and measured using advanced 3D modeling *** analyze the pelvic and soft tissue parameters,we emp-loyed statistical methods including paired sample t-tests,Wilcoxon rank-sum tests,and correlation *** The investigation highlighted significant sex disparities in 14 pelvic bone parameters and 3 soft tissue *** demonstrated larger measurements in pelvic depth and overall curvature,smaller measurements in pelvic width,a larger mesorectal fat area,and a larger anterior-posterior abdominal *** contrast,females exhibited wider pelvises,shallower depth,smaller overall curvature,and an increased amount of subcutaneous fat ***,there were no significant sex differences observed in certain parameters such as sacral curvature height,superior pubococcygeal diameter,rectal area,visceral fat area,waist circumference,and transverse abdominal *** The reconstruction of 3D CT data enabled accurate pelvic measurements,revealing significant sex differences in both pelvic and soft tissue *** study design offer potential in predicting surgical difficulties and creating personalized surgical plans for male rectal cancer patients with a potentially“difficult pelvis”,ultimately improving surgical ***

关键词： Computerized tomography Rectal cancer Three-dimensional reconstruction Pelvimetry Sex differences

LSTM Based Neural Network Model for Anomaly Event Detection in Care-Independent Smart Homes

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2689-2706页

作者： Brij B.Gupta Akshat gaurav Razaz Waheeb Attar Varsha Arya Ahmed Alhomoud Kwok Tai Chui Department of Computer Science and Information Engineering Asia UniversityTaichung413TaiwanChina Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India Computer Engineering Ronin InstituteMontclairNJ 07043USA Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Business Administration Asia UniversityTaichung413TaiwanChina Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia School of Science and Technology Hong Kong Metropolitan University(HKMU)Hong KongChina

This study introduces a long-short-term memory(LSTM)-based neural network model developed for detecting anomaly events in care-independent smart homes,focusing on the critical application of elderly fall *** balances the dataset using the Synthetic Minority Over-sampling Technique(SMOTE),effectively neutralizing bias to address the challenge of unbalanced datasets prevalent in time-series classification *** proposed LSTM model is trained on the enriched dataset,capturing the temporal dependencies essential for anomaly *** model demonstrated a significant improvement in anomaly detection,with an accuracy of 84%.The results,detailed in the comprehensive classification and confusion matrices,showed the model’s proficiency in distinguishing between normal activities and *** study contributes to the advancement of smart home safety,presenting a robust framework for real-time anomaly monitoring.

关键词： LSTM neural networks anomaly detection smart home health-care elderly fall prevention

Optimized Phishing Detection with Recurrent Neural Network and Whale Optimizer Algorithm

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Computers, Materials & Continua 2024年第9期80卷 4895-4916页

作者： Brij Bhooshan Gupta Akshat gaurav Razaz Waheeb Attar Varsha Arya Ahmed Alhomoud Kwok Tai Chui Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPuneMaharashtra411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India Ronin Institute MontclairNJ 07043USA Management Department College of Business AdministrationPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Business Administration Asia UniversityTaichung413Taiwan Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Electronic Engineering and Computer Science Hong Kong Metropolitan University(HKMU)HomantinHong KongChina

Phishing attacks present a persistent and evolving threat in the cybersecurity land-scape,necessitating the development of more sophisticated detection *** machine learning approaches to phishing detection have relied heavily on feature engineering and have often fallen short in adapting to the dynamically changing patterns of phishingUniformResource Locator(URLs).Addressing these challenge,we introduce a framework that integrates the sequential data processing strengths of a Recurrent Neural Network(RNN)with the hyperparameter optimization prowess of theWhale Optimization Algorithm(WOA).Ourmodel capitalizes on an extensive Kaggle dataset,featuring over 11,000 URLs,each delineated by 30 *** WOA’s hyperparameter optimization enhances the RNN’s performance,evidenced by a meticulous validation *** results,encapsulated in precision,recall,and F1-score metrics,surpass baseline models,achieving an overall accuracy of 92%.This study not only demonstrates the RNN’s proficiency in learning complex patterns but also underscores the WOA’s effectiveness in refining machine learning models for the critical task of phishing detection.

关键词： Phishing detection Recurrent Neural Network(RNN) Whale Optimization Algorithm(WOA) cybersecurity machine learning optimization