通过交叉验证堆栈和VAD信息检测Windows代码注入

Windows 32/64位代码注入攻击是恶意软件常用的攻击技术,在内存取证领域,现存的代码注入攻击检测技术在验证完整性方面不能处理动态内容,并且在解析内存中数据结构方面无法兼容不同版本的Windows系统。因此提出了通过交叉验证进程堆栈和VAD信息定位注入代码方法,将基于遍历栈帧得到的函数返回地址、模块名等信息结合进程VAD结构来检测函数返回地址、匹配文件名以定位注入代码,并且研发了基于Volatility取证框架的Windows代码注入攻击检测插件codefind。测试结果表明,即使在VAD节点被恶意软件修改,方法仍能够有效定位Windows 32/64位注入代码攻击。

Drift DetectionMethod Using DistanceMeasures and Windowing Schemes for Sentiment Classification

Textual data streams have been extensively used in practical applications where consumers of online products have expressed their views regarding online products.Due to changes in data distribution,commonly referred to as concept drift,mining this data stream is a challenging problem for researchers.The majority of the existing drift detection techniques are based on classification errors,which have higher probabilities of false-positive or missed detections.To improve classification accuracy,there is a need to develop more intuitive detection techniques that can identify a great number of drifts in the data streams.This paper presents an adaptive unsupervised learning technique,an ensemble classifier based on drift detection for opinion mining and sentiment classification.To improve classification performance,this approach uses four different dissimilarity measures to determine the degree of concept drifts in the data stream.Whenever a drift is detected,the proposed method builds and adds a new classifier to the ensemble.To add a new classifier,the total number of classifiers in the ensemble is first checked if the limit is exceeded before the classifier with the least weight is removed from the ensemble.To this end,a weighting mechanism is used to calculate the weight of each classifier,which decides the contribution of each classifier in the final classification results.Several experiments were conducted on real-world datasets and the resultswere evaluated on the false positive rate,miss detection rate,and accuracy measures.The proposed method is also compared with the state-of-the-art methods,which include DDM,EDDM,and PageHinkley with support vector machine(SVM)and Naive Bayes classifiers that are frequently used in concept drift detection studies.In all cases,the results show the efficiency of our proposed method.

基于Windows/RTX的实时仿测软件设计

针对传统测试软件实时性有限、传统仿真接口软件通用性程度低的问题,为满足半实物仿真软件需兼顾单元测试和控制系统仿真验证的需求,设计了基于Windows/RTX的实时仿测软件。仿测软件采用模块化的设计原则,开发了GUI层人机交互界面和RTX层实时运行程序。为保证实时性,采用无锁循环缓冲区+双线程技术,解决了RTX环境下仿真步长为1 ms时串口数据收发的超时问题;提出一种超时检测算法监测仿真节点的实时状态。借助cJSON优化了测试用例配置文件,用户可以更灵活地编辑测试用例,利用RTW自动代码生成将弹体模型编译集成到RTX仿测软件工程。实验结果表明:该仿测软件有效兼顾了单测与仿真,提高了仿测软件的通用性和二次开发效率,降低了开发难度。

Time-domain dynamic constitutive model suitable for mucky soil site seismic response

Soil nonlinear behavior displays noticeable effects on the site seismic response.This study proposes a new functional expression of the skeleton curve to replace the hyperbolic skeleton curve.By integrating shear modulus and combining the dynamic skeleton curve and the damping degradation coefficient,the constitutive equation of the logarithmic dynamic skeleton can be obtained,which considers the damping effect in a soil dynamics problem.Based on the finite difference method and the multi-transmitting boundary condition,a 1D site seismic response analysis program called Soilresp1D has been developed herein and used to analyze the time-domain seismic response in three types of sites.At the same time,this study also provides numerical simulation results based on the hyperbolic constitutive model and the equivalent linear method.The results verify the rationality of the new soil dynamic constitutive model.It can analyze the mucky soil site nonlinear seismic response,reflecting the deformation characteristics and damping effect of the silty soil.The hysteresis loop area is more extensive,and the residual strain is evident.

Time-Domain Analysis of Body Freedom Flutter Based on 6DOF Equation

The reduced weight and improved efficiency of modern aeronautical structures result in a decreasing separation of frequency ranges of rigid and elastic modes.Particularly,a high-aspect-ratio flexible flying wing is prone to body freedomflutter(BFF),which is a result of coupling of the rigid body short-periodmodewith 1st wing bendingmode.Accurate prediction of the BFF characteristics is helpful to reflect the attitude changes of the vehicle intuitively and design the active flutter suppression control law.Instead of using the rigid body mode,this work simulates the rigid bodymotion of the model by using the six-degree-of-freedom(6DOF)equation.A dynamicmesh generation strategy particularly suitable for BFF simulation of free flying aircraft is developed.An accurate Computational Fluid Dynamics/Computational Structural Dynamics/six-degree-of-freedom equation(CFD/CSD/6DOF)-based BFF prediction method is proposed.Firstly,the time-domain CFD/CSD method is used to calculate the static equilibrium state of the model.Based on this state,the CFD/CSD/6DOF equation is solved in time domain to evaluate the structural response of themodel.Then combinedwith the variable stiffnessmethod,the critical flutter point of the model is obtained.This method is applied to the BFF calculation of a flyingwing model.The calculation results of the BFF characteristics of the model agree well with those fromthe modalmethod andNastran software.Finally,the method is used to analyze the influence factors of BFF.The analysis results show that the flutter speed can be improved by either releasing plunge constraint or moving the center ofmass forward or increasing the pitch inertia.

Active and passive modulation of solar light transmittance in a uniquely multifunctional dual-band single molecule for smart window applications

Functional materials may change color by heat and electricity separately or simultaneously in smart windows.These materials have not only demonstrated remarkable potential in the modulation of solar radiation but are also leading to the development of indoor environments that are more comfortable and conducive to improving individuals'quality of life.Unfortunately,dual-responsive materials have not received ample research attention due to economic and technological challenges.As a consequence,the broader utilization of smart windows faces hindrances.To address this new generational multistimulus responsive chromic materials,our group has adopted a developmental strategy to create a poly(NIPAM)n-HV as a switchable material by anchoring active viologen(HV)onto a phase-changing poly(NIPAM)n-based smart material for better utility and activity.These constructed smart windows facilitate individualistic reversible switching,from a highly transparent state to an opaque state(thermochromic)and a red state(electrochromic),as well as facilitate a simultaneous dual-stimuli response reversible switching from a clear transparent state to a fully opaque(thermochromic)and orange(electrochromic)states.Absolute privacy can be attained in smart windows designed for exclusive settings by achieving zero transmittance.Each unique chromic mode operates independently and modulates visible and near-infrared(NIR)light in a distinct manner.Hence,these smart windows with thermal and electric dual-stimuli responsiveness demonstrate remarkable heat regulation capabilities,rendering them highly attractive for applications in building facades,energy harvesting,privacy protection,and color display.

Learning Epipolar Line Window Attention for Stereo Image Super-Resolution Reconstruction

Transformer-based stereo image super-resolution reconstruction(Stereo SR)methods have significantly improved image quality.However,existing methods have deficiencies in paying attention to detailed features and do not consider the offset of pixels along the epipolar lines in complementary views when integrating stereo information.To address these challenges,this paper introduces a novel epipolar line window attention stereo image super-resolution network(EWASSR).For detail feature restoration,we design a feature extractor based on Transformer and convolutional neural network(CNN),which consists of(shifted)window-based self-attention((S)W-MSA)and feature distillation and enhancement blocks(FDEB).This combination effectively solves the problem of global image perception and local feature attention and captures more discriminative high-frequency features of the image.Furthermore,to address the problem of offset of complementary pixels in stereo images,we propose an epipolar line window attention(EWA)mechanism,which divides windows along the epipolar direction to promote efficient matching of shifted pixels,even in pixel smooth areas.More accurate pixel matching can be achieved using adjacent pixels in the window as a reference.Extensive experiments demonstrate that our EWASSR can reconstruct more realistic detailed features.Comparative quantitative results show that in the experimental results of our EWASSR on the Middlebury and Flickr1024 data sets for 2×SR,compared with the recent network,the Peak signal-to-noise ratio(PSNR)increased by 0.37 dB and 0.34 dB,respectively.

Wideband low-scattering metasurface with an in-band reconfigurable transparent window

Active metasurfaces with dynamically reconfigurable functionalities are highly demanded in various practical applications.Here,we propose a wideband low-scattering metasurface that can realize an in-band reconfigurable transparent window by altering the operation states of the PIN diodes loaded on the structures.The metasurface is composed of a band-pass frequency selective surface(FSS)sandwiched between two polarization conversion metasurfaces(PCMs).PIN diodes are integrated into the FSS to switch the transparent window,while a checkerboard configuration is applied in PCMs for the diffusive-reflective function.A sample with 20×20 elements is designed,fabricated,and experimentally verified.Both simulated and measured results show that the in-band functions can be dynamically switched between beam-splitting scattering and high transmission by controlling the biasing states of the diodes,while low backscattering can be attained outside the passband.Furthermore,the resonant structures of FSS also play the role of feeding lines,thus significantly eliminating extra interference compared with conventional feeding networks.We envision that the proposed metasurface may provide new possibilities for the development of an intelligent stealth platform and its antenna applications.

Case Report: Surgical Correction of Transposition of the Great Arteries with Aortopulmonary Window

Introduction:Transposition of the great arteries(TGA)with aortopulmonary window is a rare type of congenital heart disease with limited experience.We reported a neonate aged 25 days receiving the arterial switch operation and assisted with extracorporeal membrane oxygenation.Conclusion:TGA with aortopulmonary window can be safely correctly with the arterial switch operation.

Bone block from lateral window-correcting vertical and horizontal bone deficiency in maxilla posterior site:A case report

BACKGROUND Lateral window approach for sinus floor lift is commonly used for vertical bone augmentation in cases when the residual bone height is less than 5 mm.However,managing cases becomes more challenging when a maxillary sinus pseudocyst is present or when there is insufficient bone width.In this case,we utilized the bone window prepared during the lateral window sinus lift as a shell for horizontal bone augmentation.This allowed for simultaneous horizontal and vertical bone augmentation immediately after the removal of the maxillary sinus pseudocyst.CASE SUMMARY A 28-year-old female presented to our clinic with the chief complaint of missing upper left posterior teeth.Intraoral examination showed a horizontal deficiency of the alveolar ridge contour.The height of the alveolar bone was approximately 3.6 mm on cone beam computed tomography(CBCT).And a typical well-defined'dome-shaped'lesion in maxillary sinus was observed on CBCT imaging.The lateral bony window was prepared using a piezo-ultrasonic device,then the bony window was fixed to the buccal side of the 26 alveolar ridge using a titanium screw with a length of 10 mm and a diameter of 1.5 mm.The space between the bony window and the alveolar ridge was filled with Bio-Oss,covered with a Bio-Gide collagen membrane,and subsequently sutured.Nine months later,the patient’s bone width increased from 4.8 to 10.5 mm,and the bone height increased from 3.6 to 15.6 mm.Subsequently,a Straumann^(■)4.1 mm×10 mm implant was placed.The final all-ceramic crown restoration was completed four months later,and both clinical and radiographic examinations showed that the implant was successful,and the patient was satisfied with the results.CONCLUSION The bone block harvested from the lateral window sinus lift can be used for simultaneous horizontal bone augmentation acting as a shell for good two-dimensional bone augmentation.

Design of Intelligent Window Automatic Monitoring System Based on Microcontroller Control

To ensure the safety of residents’lives and property by using automatic opening and closing of ordinary windows,this article designs an intelligent window automatic monitoring system.The article proposes a software and hardware design scheme for the system,which comprises a microcontroller control module,temperature and humidity detection module,harmful gas detection module,rainfall detection module,human thermal radiation induction module,Organic Light-Emitting Diode(OLED)display module,stepper motor drive module,Wi-Fi communication module,etc.Users use this system to monitor environmental data such as temperature,humidity,rainfall,harmful gas concentrations,and human health.Users can control the opening and closing of windows through manual,microcontroller,and mobile application(app)remote methods,providing users with a more convenient,comfortable,and safe living environment.

Fine-Tuning Cyber Security Defenses: Evaluating Supervised Machine Learning Classifiers for Windows Malware Detection

Malware attacks on Windows machines pose significant cybersecurity threats,necessitating effective detection and prevention mechanisms.Supervised machine learning classifiers have emerged as promising tools for malware detection.However,there remains a need for comprehensive studies that compare the performance of different classifiers specifically for Windows malware detection.Addressing this gap can provide valuable insights for enhancing cybersecurity strategies.While numerous studies have explored malware detection using machine learning techniques,there is a lack of systematic comparison of supervised classifiers for Windows malware detection.Understanding the relative effectiveness of these classifiers can inform the selection of optimal detection methods and improve overall security measures.This study aims to bridge the research gap by conducting a comparative analysis of supervised machine learning classifiers for detecting malware on Windows systems.The objectives include Investigating the performance of various classifiers,such as Gaussian Naïve Bayes,K Nearest Neighbors(KNN),Stochastic Gradient Descent Classifier(SGDC),and Decision Tree,in detecting Windows malware.Evaluating the accuracy,efficiency,and suitability of each classifier for real-world malware detection scenarios.Identifying the strengths and limitations of different classifiers to provide insights for cybersecurity practitioners and researchers.Offering recommendations for selecting the most effective classifier for Windows malware detection based on empirical evidence.The study employs a structured methodology consisting of several phases:exploratory data analysis,data preprocessing,model training,and evaluation.Exploratory data analysis involves understanding the dataset’s characteristics and identifying preprocessing requirements.Data preprocessing includes cleaning,feature encoding,dimensionality reduction,and optimization to prepare the data for training.Model training utilizes various supervised classifiers,and their performance is evaluated using metrics such as accuracy,precision,recall,and F1 score.The study’s outcomes comprise a comparative analysis of supervised machine learning classifiers for Windows malware detection.Results reveal the effectiveness and efficiency of each classifier in detecting different types of malware.Additionally,insights into their strengths and limitations provide practical guidance for enhancing cybersecurity defenses.Overall,this research contributes to advancing malware detection techniques and bolstering the security posture of Windows systems against evolving cyber threats.

快速拓展Windows实时性!史上最小的PLC运动控制器发布

为了解决Windows系统下可视化界面友好、软件开发容易、兼容性好,但无法实现实时性控制;其它带有实时控制功能的系统存在软件平台搭建困难、开发难度高、兼容性差等问题。立迈胜研发了一种NIMC301-A微型运动控制器,可以做到开箱即用,极大地增加了用户的易用性。其自带CANopen主站,具备PLC控制功能,也可为WindoWs平台提供实时性拓展,而体积仅相当于“U盘”大小!

多媒体课件在Windows系统中的个性化创意设计

文章从Windows桌面操作系统中图形界面应用出发,探讨通过个性化的设计方法创建自己的Windows Space,给用户创造出虚拟的桌面和软件界面应用,以多媒体课件的设计为实例,分析了多媒体课件界面设计的组成要素以及运用Flash和Dreamweaver进行个性化创意设计的基本步骤。

Windowing and Gapping in Imperative Sentences: on the Basis of Talmy's"Causal-chain Windowing"Approach

This paper intends to analyze the six types of English imperative sentences proposed by Chen (1984) from a perspective of causal-chain windowing. It comes to the conclusions that Talmy's causal-chain windowing approach as well as the cognitive underpinnings of causal windowing and gapping is proved to be applicable in English imperative structures, and that generally speaking, the final portion of an imperative sentence is always windowed while the intermediate portions gapped.

基于强化学习的自动化Windows域渗透方法

Windows域为用户之间的资源共享及信息交互提供统一的系统服务,在便利内网管理的同时带来了巨大的安全隐患。近年来,针对域控制器的各式攻击层出不穷,实现自动化渗透能够灵活检测Windows域中存在的漏洞威胁,保障办公网络安全稳定地持久运行,其核心是高效挖掘环境内可行的攻击路径。为此,将渗透测试过程进行强化学习建模,通过智能体与域环境的真实交互发现漏洞组合,进而验证有效的攻击序列;基于主机对渗透进程的贡献差异,减少强化学习模型中非必要的状态与动作,优化路径选择策略,提升实际攻击效率;使用状态动作删减、探索策略优化的Q学习算法筛选最优攻击路径,自动验证域环境中所有可能的安全隐患,为域管理员提供防护依据。实验针对典型内网业务场景展开测试,从生成的13种高效攻击路径中筛选最优路径,通过与相关研究成果对比,突出了所提方法在域控权限获取、主机权限获取、攻击步长、收敛性以及时间代价等方面的性能优化效果。

Windowing Techniques, the Welch Method for Improvement of Power Spectrum Estimation

This paper revisits the characteristics of windowing techniques with various window functions involved,and successively investigates spectral leakage mitigation utilizing the Welch method.The discrete Fourier transform(DFT)is ubiquitous in digital signal processing(DSP)for the spectrum analysis and can be efciently realized by the fast Fourier transform(FFT).The sampling signal will result in distortion and thus may cause unpredictable spectral leakage in discrete spectrum when the DFT is employed.Windowing is implemented by multiplying the input signal with a window function and windowing amplitude modulates the input signal so that the spectral leakage is evened out.Therefore,windowing processing reduces the amplitude of the samples at the beginning and end of the window.In addition to selecting appropriate window functions,a pretreatment method,such as the Welch method,is effective to mitigate the spectral leakage.Due to the noise caused by imperfect,nite data,the noise reduction from Welch’s method is a desired treatment.The nonparametric Welch method is an improvement on the periodogram spectrum estimation method where the signal-to-noise ratio(SNR)is high and mitigates noise in the estimated power spectra in exchange for frequency resolution reduction.The periodogram technique based on Welch method is capable of providing good resolution if data length samples are appropriately selected.The design of nite impulse response(FIR)digital lter using the window technique is rstly addressed.The inuence of various window functions on the Fourier transform spectrum of the signals is discussed.Comparison on spectral resolution based on the traditional power spectrum estimation and various window-function-based Welch power spectrum estimations is presented.

Research on Windowing Image Fusion

The speed and quality of the image fusion always restrain each other.The real-time image fusion is one of the problems which needs to be studied and solved urgently.The windowing processing technology for the image fusion proposed in this paper can solve this problem in a certain extent.The windowing rules were put forward and the applicable scope for the windowing fusion and the calculation method for the maximum windowing area were determined.And,the results of the windowing fusion were analyzed,verified and compared to confirm the feasibility of this technology.

Electrocardiogram Feature Extraction and Pattern Recognition Using a Novel Windowing Algorithm

This paper presents a Novel Windowing Algorithm for Electrocardiogram Feature Extraction and Pattern Recognition. The work presented here deals with a simple and efficient way of detecting ECG features that are P, Q, R, S and T waves. Windowing method is used to select these waves. Windows are based on varying R-R intervals. It has been tested on ECG simulator data and also on different records of the MIT-BIH arrhythmia database, producing satisfactory results. ECG timing intervals are also required for monitoring the cardiac condition of patients. Hence after feature detections ECG timing intervals like the PR interval, QRS duration, the QT interval, the QT corrected interval and Vent Rate are efficiently calculated using proposed Formulae.

An Electrochromic Nickel Phosphate Film for Large-Area Smart Window with Ultra-Large Optical Modulation

Exploring materials with high electrochemical activity is of keen interest for electrochemistry-controlled optical and energy storage devices.However,it remains a great challenge for transition metal oxides to meet this feature due to their low electron conductivity and insufficient reaction sites.Here,we propose a type of transition metal phosphate(NiHPO_(4)·3H_(2)O,NHP)by a facile and scalable electrodeposition method,which can achieve the capability of efficient ion accommodation and injection/extraction for electrochromic energy storage applications.Specifically,the NHP film with an ultra-high transmittance(approach to 100%)achieves a large optical modulation(90.8%at 500 nm),high coloration efficiency(75.4 cm^(2)C^(-1)at 500 nm),and a high specific capacity of 47.8 mAh g^(-1)at 0.4 A g^(-1).Furthermore,the transformation mechanism of NHP upon electrochemical reaction is systematically elucidated using in situ and ex situ techniques.Ultimately,a large-area electrochromic smart window with 100 cm^(2)is constructed based on the NHP electrode,displaying superior electrochromic energy storage performance in regulating natural light and storing electrical charges.Our findings may open up new strategies for developing advanced electrochromic energy storage materials and smart windows.