Automobile power windows are mechanisms that can be opened and shut with the press of a button.Although these windows can comfort the effort of occupancy to move the window,failure to recognize the person’s body part...Automobile power windows are mechanisms that can be opened and shut with the press of a button.Although these windows can comfort the effort of occupancy to move the window,failure to recognize the person’s body part at the right time will result in damage and in some cases,loss of that part.An anti-pinch mechanism is an excellent choice to solve this problem,which detects the obstacle in the glass path immediately and moves it down.In this paper,an optimal solution H_/H_(∞)is presented for fault detection of the anti-pinch window system.The anti-pinch makes it possible to detect an obstacle and prevent damages through sampling parameters such as current consumption,the speed and the position of DC motors.In this research,a speed-based method is used to detect the obstacles.In order to secure the anti-pinch window,an optimal algorithm based on a fault detection observer is suggested.In the residual design,the proposed fault detection algorithm uses theDCmotor angular velocity rate.Robustness against disturbances and sensitivity to the faults are considered as an optimization problem based on Multi-Objective Particle Swarm Optimization algorithm.Finally,an optimal filter for solving the fault problem is designed using the H_/H_(∞)method.The results show that the simulated anti-pinch window is pretty sensitive to the fault,in the sense that it can detect the obstacle in 50 ms after the fault occurrence.展开更多
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...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。展开更多
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...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.展开更多
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 ...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.展开更多
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...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.展开更多
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 comp...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.展开更多
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 reconfigurabl...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.展开更多
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 opera...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.展开更多
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 m...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.展开更多
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,...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.展开更多
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 thre...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.展开更多
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 a...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.展开更多
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 malwar...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.展开更多
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 approxi...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.展开更多
基金supported by DP-FTSM-2021,Dana Lonjakan Penerbitan FTSM,UKM.
文摘Automobile power windows are mechanisms that can be opened and shut with the press of a button.Although these windows can comfort the effort of occupancy to move the window,failure to recognize the person’s body part at the right time will result in damage and in some cases,loss of that part.An anti-pinch mechanism is an excellent choice to solve this problem,which detects the obstacle in the glass path immediately and moves it down.In this paper,an optimal solution H_/H_(∞)is presented for fault detection of the anti-pinch window system.The anti-pinch makes it possible to detect an obstacle and prevent damages through sampling parameters such as current consumption,the speed and the position of DC motors.In this research,a speed-based method is used to detect the obstacles.In order to secure the anti-pinch window,an optimal algorithm based on a fault detection observer is suggested.In the residual design,the proposed fault detection algorithm uses theDCmotor angular velocity rate.Robustness against disturbances and sensitivity to the faults are considered as an optimization problem based on Multi-Objective Particle Swarm Optimization algorithm.Finally,an optimal filter for solving the fault problem is designed using the H_/H_(∞)method.The results show that the simulated anti-pinch window is pretty sensitive to the fault,in the sense that it can detect the obstacle in 50 ms after the fault occurrence.
基金financially supported by the National Natural Science Foundation of China(52072409)the Major Scientific and Technological Innovation Project of Shandong Province(2020CXGC010403)+1 种基金the Taishan Scholar Project(No.ts201712020)the Natural Science Foundation of Shandong Province(ZR2021QE062)
文摘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.
基金supported by the National Research Foundation (NRF)grants funded by the Ministry of Education (2020R1A6A1A03038817),Republic of Korea。
文摘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.
基金This work was supported by Sichuan Science and Technology Program(2023YFG0262).
文摘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.
基金supported by the MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2024-RS-2024-00437494)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation).
文摘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.
基金Project supported by the Joint Fund of Ministry of Education for Equipment Pre-research (Grant No. 8091B032112)the National Natural Science Foundation of China (Grant Nos. 62271243 and 62071215)+2 种基金the Priority Academic Program Development of Jiangsu Higher Education Institutionsthe Fundamental Research Funds for the Central UniversitiesJiangsu Provincial Key Laboratory of Advanced Manipulating Technique of Electromagnetic Wave
文摘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.
文摘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.
文摘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.
基金supported by Natural Science Foundation Project of Gansu Provincial Science and Technology Department(No.1506RJZA084)Gansu Provincial Education Department Scientific Research Fund Grant Project(No.1204-13).
文摘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.
基金Sponsored by the National Natural Science Foundation of China(52278045).
文摘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.
文摘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.
基金This researchwork is supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2024R411),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘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.
文摘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.