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。

Bimetallic In_(2)O_(3)/Bi_(2)O_(3) Catalysts Enable Highly Selective CO_(2) Electroreduction to Formate within Ultra-Broad Potential Windows

CO_(2)electrochemical reduction reaction(CO_(2)RR)to formate is a hopeful pathway for reducing CO_(2)and producing high-value chemicals,which needs highly selective catalysts with ultra-broad potential windows to meet the industrial demands.Herein,the nanorod-like bimetallic ln_(2)O_(3)/Bi_(2)O_(3)catalysts were successfully synthesized by pyrolysis of bimetallic InBi-MOF precursors.The abundant oxygen vacancies generated from the lattice mismatch of Bi_(2)O_(3)and ln_(2)O_(3)reduced the activation energy of CO_(2)to*CO_(2)·^(-)and improved the selectivity of*CO_(2)·^(-)to formate simultaneously.Meanwhile,the carbon skeleton derived from the pyrolysis of organic framework of InBi-MOF provided a conductive network to accelerate the electrons transmission.The catalyst exhibited an ultra-broad applied potential window of 1200 mV(from-0.4 to-1.6 V vs RHE),relativistic high Faradaic efficiency of formate(99.92%)and satisfactory stability after 30 h.The in situ FT-IR experiment and DFT calculation verified that the abundant oxygen vacancies on the surface of catalysts can easily absorb CO_(2)molecules,and oxygen vacancy path is dominant pathway.This work provides a convenient method to construct high-performance bimetallic catalysts for the industrial application of CO_(2)RR.

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。

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.

AI-Driven Prioritization and Filtering of Windows Artifacts for Enhanced Digital Forensics

Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised systems.Forensic analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather evidence.Therefore,forensic analysts must sift through extensive datasets to isolate pertinent evidence.However,manually identifying suspicious traces among numerous artifacts is time-consuming and labor-intensive.Previous studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital forensics.Despite the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific evaluations.In this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital forensics.Our system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly detection.The key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic entropy.Our evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative approaches.Our system can significantly reduce the time required for forensic analysis and serve as a reference for future studies.

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.

Vehicle routing optimization algorithm based on time windows and dynamic demand

To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.

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.

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.

Window Views of Wards in Foreign Hospitals

Through the collection and systematic analysis of documents related to window views of hospitals,it is found that natural window views had a significant impact on patients’health benefits.The research focused on three aspects:“shortening length of stay”,“pain reduction”and“improvement of recovery rate”,mainly covering three types of patients:“heart patients”,“postoperative patients”and“patients of rehabilitation centers”.Based on the above analysis,summary and sorting,new directions and perspectives of hospital environment design and research under the concept of comprehensive health of people’s physiological,psychological and social adaptation will be obtained to provide references for the research and practice of health architecture,rehabilitation architecture,biophile design and other fields.

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.

基于Windows和Linux操作系统基线核查及加固技术的研究和应用

文章对Windows和Linux操作系统基线核查加固技术进行研究。针对电力系统主机存在的安全缺陷,从主机信息、账户及口令、主机配置、服务及应用以及日志及审计等五个大类着手,给出自动化基线核查与加固工具的总体开发架构与模块设计,重点阐述2种操作系统基线安全与加固以及数据分析等核心功能的开发流程,经测试证明了该工具的可用性和健壮性。

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.

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!

畅玩3A、能装Windows和Linux!国产处理器KX-7000测评来了

近日,有第三方媒体发布了关于兆芯KX-7000的评测视频,认为KX-7000不仅是目前桌面端最强的国产处理器之一,对于普通用户来说,也是最易上手的一款国产CPU。KX-7000是兆芯最新一代的国产X86处理器,部分海外网站媒体(如PC Watch)对其进行了性能测试并发布了结果。测试内容围绕KX-7000的架构、性能及主流应用方面进行了测试,在介绍了兆芯x86架构来源及特点的同时,展现了KX-7000在Spec2006、视频编解码、3A游戏、主流办公等应用下的数据与体验。具体如下。

Integrating Virtual Reality and Energy Analysis with BIM to Optimize Window-to-Wall Ratio and Building’s Orientation for Age-in-Place Design at the Conceptual Stage

This study unfolds an innovative approach aiming to address the critical role of building design in global energy consumption, focusing on optimizing the Window-to-Wall Ratio (WWR), since buildings account for approximately 30% of total energy consumed worldwide. The greatest contributors to energy expenditure in buildings are internal artificial lighting and heating and cooling systems. The WWR, determined by the proportion of the building’s glazed area to its wall area, is a significant factor influencing energy efficiency and minimizing energy load. This study introduces the development of a semi-automated computer model designed to offer a real-time, interactive simulation environment, fostering improving communication and engagement between designers and owners. The said model serves to optimize both the WWR and building orientation to align with occupants’ needs and expectations, subsequently reducing annual energy consumption and enhancing the overall building energy performance. The integrated model incorporates Building Information Modeling (BIM), Virtual Reality (VR), and Energy Analysis tools deployed at the conceptual design stage, allowing for the amalgamation of owners’ inputs in the design process and facilitating the creation of more realistic and effective design strategies.

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。

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。

Development of RF windows for 650 MHz multibeam klystron

Radio frequency windows are developed and evaluated for a 650 MHz continuous-wave multibeam klystron.Thin-pillbox windows with alumina and beryllia disks are designed with an average RF power of CW 400 kW.Results of a cold test and tuning procedures are described.The final measured S11 curves under the required bandwidth are less than-32.0 and-26.9 dB for alumina and beryllia windows,respectively.The windows are tested up to CW 143 kW for traveling waves and CW 110 kW for standing waves using a solid-state amplifier as an RF power source.Multipactor simulations for windows and benchmark studies for the thermal analysis of ceramic disks are introduced.