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Intrumer:A Multi Module Distributed Explainable IDS/IPS for Securing Cloud Environment

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Computers, Materials & Continua 2025年第1期82卷 579-607页

作者： Nazreen banu A S.K.b.Sangeetha Department of Computer Science and Engineering SRM Institute of Science and TechnologyVadapalani CampusChennai600026Tamil NaduIndia

The increasing use of cloud-based devices has reached the critical point of cybersecurity and unwanted network *** environments pose significant challenges in maintaining privacy and *** approaches,such as IDS,have been developed to tackle these ***,most conventional Intrusion Detection System(IDS)models struggle with unseen cyberattacks and complex high-dimensional *** fact,this paper introduces the idea of a novel distributed explainable and heterogeneous transformer-based intrusion detection system,named INTRUMER,which offers balanced accuracy,reliability,and security in cloud settings bymultiplemodulesworking together within *** traffic captured from cloud devices is first passed to the TC&TM module in which the Falcon Optimization Algorithm optimizes the feature selection process,and Naie bayes algorithm performs the classification of *** selected features are classified further and are forwarded to the Heterogeneous Attention Transformer(HAT)*** this module,the contextual interactions of the network traffic are taken into account to classify them as normal or malicious *** classified results are further analyzed by the Explainable Prevention Module(XPM)to ensure trustworthiness by providing interpretable *** the explanations fromthe classifier,emergency alarms are transmitted to nearby IDSmodules,servers,and underlying cloud devices for the enhancement of preventive *** experiments on benchmark IDS datasets CICIDS 2017,Honeypots,and NSL-KDD were conducted to demonstrate the efficiency of the INTRUMER model in detecting network trafficwith high accuracy for different *** outperforms state-of-the-art approaches,obtaining better performance metrics:98.7%accuracy,97.5%precision,96.3%recall,and 97.8%*** results validate the robustness and effectiveness of INTRUMER in securing diverse cloud environments against sophisticated cyber threats.

关键词： Cloud computing intrusion detection system transformers and explainable artificial intelligence(XAI)

Neuroinflammation revisited through the microglial lens

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Neural Regeneration Research 2025年第7期20卷 1989-1990页

作者： Renato Socodato João b.Relvas Institute of Research and Innovation in Health(i3S)and Institute for Molecular and Cell biology(IbMC) University of PortoPortoPortugal Department of biomedicine Faculty of Medicine of the University of Porto(FMUP)PortoPortugal

Neuroimmunology is emerging as a pivotal field,shedding light on the intricate dialogues between the central nervous system(CNS)and the immune *** exploration is particularly significant in understanding microglia,the CNS’s innate immune cells,beyond the conventional conflation of“neuroinflammation”and“microglial activation.”This conflation has clouded the true complexity of these processes,potentially stalling scientific progress and the development of new *** challenge the long-standing perspectives that have oversimplified these interactions,advocating for a deeper exploration of the dynamic relationship between neuroinflammation and microglial *** dissecting specific molecular pathways,we aim to illuminate their elaborate roles in neuroinflammatory responses,especially in the context of Alzheimer’s disease(AD).Here,neuroinflammation is not merely a passive observer or a direct antagonist but a complex agent in the disease’s *** article calls for a significant paradigm shift towards an integrative,multi-omics approach to *** such a comprehensive framework is crucial for advancing our understanding of neuroinflammatory conditions and paving the way for targeted therapeutic strategies for brain diseases.

关键词： inflammation simplified activation

Federated Learning’s Role in Next-Gen TV Ad Optimization

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Computers, Materials & Continua 2025年第1期82卷 675-712页

作者： Gabriela Dobrita Simona-Vasilica Oprea Adela bâra Department of Economic Informatics and Cybernetics Bucharest University of Economic StudiesBucharest010374Romania

In the rapidly evolving landscape of television advertising,optimizing ad schedules to maximize viewer engagement and revenue has become *** methods often operate in silos,limiting the potential insights gained from broader data analysis due to concerns over privacy and data *** article introduces a novel approach that leverages Federated Learning(FL)to enhance TV ad schedule optimization,combining the strengths of local optimization techniques with the power of global Machine Learning(ML)models to uncover actionable insights without compromising data *** combines linear programming for initial ads scheduling optimization with ML—specifically,a K-Nearest Neighbors(KNN)model—for predicting ad spot *** into account the diversity and the difficulty of the ad-scheduling problem,we propose a prescriptivepredictive approach in which first the position of the ads is optimized(using Google’s OR-Tools CP-SAT)and then the scheduled position of all ads will be the result of the optimization ***,this output becomes the target of a predictive task that predicts the position of new entries based on their characteristics ensuring the implementation of the scheduling at large scale(using KNN,Light Gradient boosting Machine and Random Forest).Furthermore,we explore the integration of FL to enhance predictive accuracy and strategic insight across different broadcasting networks while preserving data *** FL approach resulted in 8750 ads being precisely matched to their optimal category placements,showcasing an alignment with the intended diversity ***,there was a minimal deviation observed,with 1133 ads positioned within a one-category variance from their ideal placement in the original dataset.

关键词： Ad scheduling prescriptive-predictive approach federated learning KNN

Transient thermal analysis as measurement method for IC package structural integrity

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Chinese Physics b 2015年第6期24卷 47-64页

作者： Alexander Han Maximilian Schmid E Liu Gordon elger Technische Hochschule Ingolstadt

Practices of IC package reliability testing are reviewed briefly, and the application of transient thermal analysis is examined in great depth. For the design of light sources based on light emitting diode （LED） efficient and accurate reliability testing is required to realize the potential lifetimes of 105 h. Transient thermal analysis is a standard method to determine the transient thermal impedance of semiconductor devices, e.g. power electronics and LEDs. The temperature of the semiconductor junctions is assessed by time-resolved measurement of their forward voltage （Vf）. The thermal path in the IC package is resolved by the transient technique in the time domain. This enables analyzing the structural integrity of the semiconductor package. However, to evaluate thermal resistance, one must also measure the dissipated energy of the device （i.e., the thermal load） and the k-factor. This is time consuming, and measurement errors reduce the accuracy. To overcome these limitations, an innovative approach, the relative thermal resistance method, was developed to reduce the measurement effort, increase accuracy and enable automatic data evaluation. This new way of evaluating data simplifies the thermal transient analysis by eliminating measurement of the k-factor and thermal load, i.e. measurement of the lumen flux for LEDs, by normalizing the transient Vf data. This is especially advantageous for reliability testing where changes in the thermal path, like cracks and delaminations, can be determined without measuring the k-factor and thermal load. Different failure modes can be separated in the time domain. The sensitivity of the method is demonstrated by its application to high- power white InGaN LEDs. For detailed analysis and identification of the failure mode of the LED packages, the transient signals are simulated by time-resolved finite element （FE） simulations. Using the new approach, the transient thermal analysis is enhanced to a powerful tool for reliability

关键词： transient thermal analysis thermal resistance reliability light emitting diode

Nano-Enhanced Dairy Scum biodiesel blends:Unleashing the Power of Aluminium Oxide for Sustainable and Efficient Engine Performance

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Journal of Thermal Science 2025年第1期34卷 283-302页

作者： Veeranna MODI Prasad b.RAMPURE Sunil Kumar SHETTY Madeva NAGARAL Channa Keshava NAIK N Johar MGM Muhammad Irsyad AbDULLAH Abdullah I.AL-MANSOUR Shamshad ALAM KLE College of Engineering and Technology ChikodiVisvesvaraya Technological University Nitte (Deemed to be University) NMAM Institute of Technology (NMAMIT)Department of Mechanical Engineering Aircraft Research and Design Centre HAL Department of Mechanical Engineering BGS College of Engineering and TechnologyBengaluruAffiliated to Visvesvaraya Technological University Management and Science University Department of Civil Engineering College of EngineeringKing Saud University

This study investigates the effect of aluminium oxide nanoparticlesaddition to biodiesel blends made from dairy milk scum on performance and combustion characteristics of the diesel *** dispersion of Al2O3nanoparticles in b20 blends at different concentrations was done with the help of *** number of blends were prepared for the *** Machine learning algorithms(Random Forest（RF）and Catboost) was used for the *** results show that in comparison to biodiesel blends without nanoparticles,the kinematic viscosity and density is higher for fuel blends with *** these Fuel blends have higher calorific *** blends exhibited reduced brake Specific Fuel Consumption（bSFC） of2.85% than the blends without nano particles(Dairy Scum Methyl Ester biodiesel 20%+Neat Diesel 80%（in volume）,DSMEb20),57.14% less CO,40.8% less hydrocarbon,and increased NOxemissions compared to conventional diesel,contributing to the development of environmentally friendly and renewable biofuel blends with *** b20NP30 is the optimal blend for performance and emission *** study concludes with findings on enhanced brake Thermal Efficiency（bTE） of 26.29% in 3×10-5（in volume） Al2O3nanoparticle-blended DSME b20 and other DSME b20 fuel blends,emphasizing the importance of optimal nanoparticle *** correlation matrix shows how engine load,efficiency measures（bTE,bSFC）,and emissions（CO,CO2,NOx,Smoke） are connected in complex *** results help us understand the complicated dynamics of engine performance and emission characteristics ***'s diagram for bTE and bSFC shows that Catboost-based bTE models perform superior to RF-based models during the training as well as testing *** results were obtained for CO and CO2emission results.

关键词： Al2O3 concentration CI engine Dairy Scum Methyl Ester biodiesel

A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol Geetika Jain Saxena Amit Pundir Sanjeev Singh Akshat Gaurav Savi bansal Razaz Waheeb Attar Mosiur Rahman brij b.Gupta Institute of Informatics and Communication University of DelhiDelhi110021India Maharaja Agrasen College University of DelhiDelhi110096India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of Research and Innovation Insights2TechinfoJaipur302001India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia CCRI&Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

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Dadaismus

Dadaismus

动情周期和妊娠期豚鼠宫颈张力的变化与性激素水平的关系

作者： elger Dietmar. Grosenick Uta.

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生殖与避孕 1990年第2期10卷 10-15页

作者：施少清 Chwalisz K elger W 国家计划生育委员会科学技术研究所 Endocrinopharmacology I. Schering AG

本文用离体宫颈张力测定法及放射免疫测定法证实,动情周期中豚鼠宫颈张力的变化与血中孕酮水平呈正相关。妊娠期豚鼠宫颈张力变化明显。孕62天及65天时,宫颈张力极度减弱,宫颈口开大,耻骨联合松弛,宫颈增重,这些生理变化是受血中P、E_2... 详细信息

本文用离体宫颈张力测定法及放射免疫测定法证实,动情周期中豚鼠宫颈张力的变化与血中孕酮水平呈正相关。妊娠期豚鼠宫颈张力变化明显。孕62天及65天时,宫颈张力极度减弱,宫颈口开大,耻骨联合松弛,宫颈增重,这些生理变化是受血中P、E_2、PGFM及羊水中PGFM浓度的影响。

关键词：豚鼠动情期妊娠期宫颈张力

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柔性装配模式下飞机薄壁件装配偏差分析

机械工程师 2025年第1期 41-45,51页

作者：乔康壮a曲学军b 沈阳航空航天大学航空宇航学院沈阳110136 沈阳航空航天大学航空制造工艺数字化国防重点学科实验室沈阳110136

针对柔性装配模式下飞机薄壁件的装配特点,综合考虑薄壁件的制造偏差、柔性工装的定位偏差及柔性件在装配力作用下的变形误差,提出一种基于柔性装配的飞机薄壁件装配偏差模型。首先,结合柔性工装定位偏差,通过确定性定位法对薄壁件发生... 详细信息

针对柔性装配模式下飞机薄壁件的装配特点,综合考虑薄壁件的制造偏差、柔性工装的定位偏差及柔性件在装配力作用下的变形误差,提出一种基于柔性装配的飞机薄壁件装配偏差模型。首先,结合柔性工装定位偏差,通过确定性定位法对薄壁件发生转动和平动产生的刚性偏差进行分析,并利用影响系数法和超元刚度矩阵理论对薄壁件因夹紧和铆接装配而产生的柔性变形进行分析。其次,针对薄壁件偏差传递规律建立了装配偏差模型,利用MATLAb求解可得到薄壁件上各关键特性点的法向偏差,对装配体最终偏差进行了有效预测。最后,通过某型飞机薄壁件进行实例验证,并借助有限元分析软件AbAQUS对薄壁件装配过程进行仿真。通过对关键测点装配偏差的计算结果和仿真结果对比,验证了文中提出的飞机薄壁件装配偏差模型的可行性。

关键词：飞机薄壁件装配偏差模型影响系数法超元刚度矩阵有限元分析