Face liveness detection is essential for securing biometric authentication systems against spoofing attacks,including printed photos,replay videos,and 3D masks.This study systematically evaluates pre-trained CNN model...Face liveness detection is essential for securing biometric authentication systems against spoofing attacks,including printed photos,replay videos,and 3D masks.This study systematically evaluates pre-trained CNN models—DenseNet201,VGG16,InceptionV3,ResNet50,VGG19,MobileNetV2,Xception,and InceptionResNetV2—leveraging transfer learning and fine-tuning to enhance liveness detection performance.The models were trained and tested on NUAA and Replay-Attack datasets,with cross-dataset generalization validated on SiW-MV2 to assess real-world adaptability.Performance was evaluated using accuracy,precision,recall,FAR,FRR,HTER,and specialized spoof detection metrics(APCER,NPCER,ACER).Fine-tuning significantly improved detection accuracy,with DenseNet201 achieving the highest performance(98.5%on NUAA,97.71%on Replay-Attack),while MobileNetV2 proved the most efficient model for real-time applications(latency:15 ms,memory usage:45 MB,energy consumption:30 mJ).A statistical significance analysis(paired t-tests,confidence intervals)validated these improvements.Cross-dataset experiments identified DenseNet201 and MobileNetV2 as the most generalizable architectures,with DenseNet201 achieving 86.4%accuracy on Replay-Attack when trained on NUAA,demonstrating robust feature extraction and adaptability.In contrast,ResNet50 showed lower generalization capabilities,struggling with dataset variability and complex spoofing attacks.These findings suggest that MobileNetV2 is well-suited for low-power applications,while DenseNet201 is ideal for high-security environments requiring superior accuracy.This research provides a framework for improving real-time face liveness detection,enhancing biometric security,and guiding future advancements in AI-driven anti-spoofing techniques.展开更多
Fingerprint-spoofing attack often occurs when imposters gain access illegally by using artificial fingerprints,which are made of common fingerprint materials,such as silicon,latex,etc.Thus,to protect our privacy,many ...Fingerprint-spoofing attack often occurs when imposters gain access illegally by using artificial fingerprints,which are made of common fingerprint materials,such as silicon,latex,etc.Thus,to protect our privacy,many fingerprint liveness detection methods are put forward to discriminate fake or true fingerprint.Current work on liveness detection for fingerprint images is focused on the construction of complex handcrafted features,but these methods normally destroy or lose spatial information between pixels.Different from existing methods,convolutional neural network(CNN)can generate high-level semantic representations by learning and concatenating low-level edge and shape features from a large amount of labeled data.Thus,CNN is explored to solve the above problem and discriminate true fingerprints from fake ones in this paper.To reduce the redundant information and extract the most distinct features,ROI and PCA operations are performed for learned features of convolutional layer or pooling layer.After that,the extracted features are fed into SVM classifier.Experimental results based on the LivDet(2013)and the LivDet(2011)datasets,which are captured by using different fingerprint materials,indicate that the classification performance of our proposed method is both efficient and convenient compared with the other previous methods.展开更多
Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artifici...Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artificial fingerprints can trick the fingerprint authentication system and access information using real users' identification.Therefore,a fingerprint liveness detection algorithm needs to be designed to prevent illegal users from accessing privacy information.In this paper,a new software-based liveness detection approach using multi-scale local phase quantity(LPQ) and principal component analysis(PCA) is proposed.The feature vectors of a fingerprint are constructed through multi-scale LPQ.PCA technology is also introduced to reduce the dimensionality of the feature vectors and gain more effective features.Finally,a training model is gained using support vector machine classifier,and the liveness of a fingerprint is detected on the basis of the training model.Experimental results demonstrate that our proposed method can detect the liveness of users' fingerprints and achieve high recognition accuracy.This study also confirms that multi-resolution analysis is a useful method for texture feature extraction during fingerprint liveness detection.展开更多
Aim to countermeasure the presentation attack for iris recognition system,an iris liveness detection scheme based on batch normalized convolutional neural network(BNCNN)is proposed to improve the reliability of the ir...Aim to countermeasure the presentation attack for iris recognition system,an iris liveness detection scheme based on batch normalized convolutional neural network(BNCNN)is proposed to improve the reliability of the iris authentication system.The BNCNN architecture with eighteen layers is constructed to detect the genuine iris and fake iris,including convolutional layer,batch-normalized(BN)layer,Relu layer,pooling layer and full connected layer.The iris image is first preprocessed by iris segmentation and is normalized to 256×256 pixels,and then the iris features are extracted by BNCNN.With these features,the genuine iris and fake iris are determined by the decision-making layer.Batch normalization technique is used in BNCNN to avoid the problem of over fitting and gradient disappearing during training.Extensive experiments are conducted on three classical databases:the CASIA Iris Lamp database,the CASIA Iris Syn database and Ndcontact database.The results show that the proposed method can effectively extract micro texture features of the iris,and achieve higher detection accuracy compared with some typical iris liveness detection methods.展开更多
Contactless verification is possible with iris biometric identification,which helps prevent infections like COVID-19 from spreading.Biometric systems have grown unsteady and dangerous as a result of spoofing assaults ...Contactless verification is possible with iris biometric identification,which helps prevent infections like COVID-19 from spreading.Biometric systems have grown unsteady and dangerous as a result of spoofing assaults employing contact lenses,replayed the video,and print attacks.The work demonstrates an iris liveness detection approach by utilizing fragmental coefficients of Haar transformed Iris images as signatures to prevent spoofing attacks for the very first time in the identification of iris liveness.Seven assorted feature creation ways are studied in the presented solutions,and these created features are explored for the training of eight distinct machine learning classifiers and ensembles.The predicted iris liveness identification variants are evaluated using recall,F-measure,precision,accuracy,APCER,BPCER,and ACER.Three standard datasets were used in the investigation.The main contribution of our study is achieving a good accuracy of 99.18%with a smaller feature vector.The fragmental coefficients of Haar transformed iris image of size 8∗8 utilizing random forest algorithm showed superior iris liveness detection with reduced featured vector size(64 features).Random forest gave 99.18%accuracy.Additionally,conduct an extensive experiment on cross datasets for detailed analysis.The results of our experiments showthat the iris biometric template is decreased in size tomake the proposed framework suitable for algorithmic verification in real-time environments and settings.展开更多
In this paper, we study the supervisory control problem of discrete event systems assuming that cyber-attacks might occur. In particular, we focus on the problem of liveness enforcement and consider a sensor-reading m...In this paper, we study the supervisory control problem of discrete event systems assuming that cyber-attacks might occur. In particular, we focus on the problem of liveness enforcement and consider a sensor-reading modification attack(SM-attack) that may disguise the occurrence of an event as that of another event by intruding sensor communication channels. To solve the problem, we introduce non-deterministic supervisors in the paper, which associate to every observed sequence a set of possible control actions offline and choose a control action from the set randomly online to control the system. Specifically, given a bounded Petri net(PN) as the reference formalism and an SMattack, an algorithm that synthesizes a liveness-enforcing nondeterministic supervisor tolerant to the SM-attack is proposed for the first time.展开更多
This paper deals with the supervisory control problem of discrete event systems modeled by labeled Petri nets. The system is originally unbounded. First, the solvability of the problem is confirmed. A necessary condit...This paper deals with the supervisory control problem of discrete event systems modeled by labeled Petri nets. The system is originally unbounded. First, the solvability of the problem is confirmed. A necessary condition is given and proven for the existence of a feasible priority-based controller based on the notions of liveness and transition invariants. Next, a cyclic behavior graph is constructed, which shows the reachable markings that guarantee the maximum liveness of the system within a given bound vector. Finally, an on-line control strategy is proposed to enforce boundedness and liveness to the given system by appending priority relations to transitions. The dynamic priority relation changes flexibly according to the current state of the system and enforces the system evolving in a bounded and live manner. In addition, numerical examples are studied to verify the validity of the proposed approach that remains the structure of the plant net and is efficient for on-line control.展开更多
The probabilities for the technology to be spoofed are widely acknowledged in biometric verification system. Important efforts have been conducted to study such threats and to develop countermeasures to direct attacks...The probabilities for the technology to be spoofed are widely acknowledged in biometric verification system. Important efforts have been conducted to study such threats and to develop countermeasures to direct attacks to the biometric verification system to ensure the security of these systems against spoof attacks and reduce this risk, by using another module that is added to the biometric verification system called the “liveness detection” which uses different anatomical properties to distinguish between real and fake traits. Thus, the robustness of the system against direct attacks can be improved through increasing the security level offered to the final user. This paper is an attempt to construct support biometric security system to protect the iris biometric verification system from spoof attacks, through integrating the iris verification system with addition module called liveness detection which composed of two sub-modules (static and dynamic). A test has been performed, for iris verification phase performed on two types of database (MMU DB) for 180 samples and (CASIA DB) for 90 samples, and gave accuracy (99.44%) with FAR of (0.0277) and FRR (0.0055) for MMU DB, and accuracy (97.77%) with FAR of (0.0333) and FRR (0.0222) for CASIA DB.展开更多
Multi-living agent system （MLAS） is a new concept in the field of complex system research, which is peculiarly suitable for the design and analysis of a complex information system in a serious confrontation and tigh...Multi-living agent system （MLAS） is a new concept in the field of complex system research, which is peculiarly suitable for the design and analysis of a complex information system in a serious confrontation and tight constraint environment. However, the universal method to quantitatively measure the living degree of an MLAS remains uncertain, which is critical to the self-organizing process. Therefore, a novel analytic hierarchy process （AHP） based method with dependent pairwise comparison matrix （PCM） for the evaluation of living degree of the MLAS is proposed, which eliminates the shortcoming of fixed PCM in traditional process. Furthermore, to avoid the annoying procedure of the consistency validation, the PCMs are appropriately reconstructed. Through an illustration of the netted radar system, the calculation detail is explicitly presented. Altogether, the advanced evaluation method successfully accomplishes the preset objective and promotes the development of the MLAS theory and AHP as well.展开更多
This paper proposes an approach to making livehess model checking problems under fairness feasible.The proposed method divides such a problem into smaller ones that can be conquered.It is not superior to existing tool...This paper proposes an approach to making livehess model checking problems under fairness feasible.The proposed method divides such a problem into smaller ones that can be conquered.It is not superior to existing tools dedicated to model checking liveness properties under fairness assumptions in terms of model checking performance but has the following positive aspects:1)the approach can be used to model check liveness properties under anti-fairness assumptions as well as fairness assumptions,2)the approach can help humans better understand the reason why they need to use fairness and/or anti-fairness assumptions,and 3)the approach makes it possible to use existing linear temporal logic model checkers to model check liveness properties under fairness and/or anti-fairness assumptions.展开更多
Several liveness theorems for GFC (the generalized free choice) systems in a reductive approach are presented.What is interesting is that the characterization is just based on deadlocks,rather than on both deadlocks a...Several liveness theorems for GFC (the generalized free choice) systems in a reductive approach are presented.What is interesting is that the characterization is just based on deadlocks,rather than on both deadlocks and traps as Commoner characterizes the liveness of ordinary free-choice systems.Several proof techniques which may be useful for proving liveness of other types of net systems are also introduced.展开更多
The significant features concerning liveness of generalized free-choice (GFC) systems are discussed.These features provide a sound basis for analyzing liveness of GFC systems in a reductive approach.What is interestin...The significant features concerning liveness of generalized free-choice (GFC) systems are discussed.These features provide a sound basis for analyzing liveness of GFC systems in a reductive approach.What is interesting is that the characterization is just based on deadlocks,rather than on both deadlocks and traps as Commoner characterizes the liveness of ordinary free-choice systems.Several proof techniques for proving liveness-related features of GFC systems are introduced.展开更多
In this paper, the Extended Strong Asymmetric Choice Nets Ⅱ (ESACN Ⅱ), a subclass of Asymmetric Choice Nets (ACN) including Extended Free Choice Nets (EFCN) and Strong Asymmetric Choke Nets Ⅱ (SACN Ⅱ, is presented...In this paper, the Extended Strong Asymmetric Choice Nets Ⅱ (ESACN Ⅱ), a subclass of Asymmetric Choice Nets (ACN) including Extended Free Choice Nets (EFCN) and Strong Asymmetric Choke Nets Ⅱ (SACN Ⅱ, is presented. A necessary and sufficient condition for liveness of ESACN Ⅱ is proposed. Moreover, a criterion is introduced, which is necessary and sufficient for judgement of liveness and boundedness of ESACN Ⅱ. Meanwhile a polynomial time algorithm is given to decide liveness and boundedness for ESACN Ⅱ.展开更多
BACKGROUND Robotic assistance is increasingly used for donor and recipient hepatectomy in liver transplantation,yet existing evidence is fragmented and variably indirect.AIM To evaluate clinical outcomes,surgical perf...BACKGROUND Robotic assistance is increasingly used for donor and recipient hepatectomy in liver transplantation,yet existing evidence is fragmented and variably indirect.AIM To evaluate clinical outcomes,surgical performance,and economic effects of robotic-assisted donor and recipient hepatectomy in the transplant pathway.METHODS Following Preferred Reporting Items for Systematic reviews and Meta-Analyses 2020 and a priori registration,systematic reviews were included with or without meta-analysis.Four databases were searched through July 2025.Methodological quality was appraised with a measurement tool to assess systematic reviews(AMSTAR 2),and certainty was graded with grading of recommendations assessment,development and evaluation(GRADE).Evidence overlap was calculated via a citation-matrix-based corrected covered area(CCA).Effect sizes were prespecified as risk ratios(RR)for dichotomous outcomes and mean differences for continuous outcomes.RESULTS Five reviews met the inclusion criteria,four with meta-analyses and one consensus review used only for context.Donor(direct)findings were more favorable for robotics in terms of estimated blood loss(≈-117 mL)and length of stay(≈-0.6 days),although with longer operative time(≈+105 minutes).Absolute risks for donor complications were not estimable from ratio-only data.Recipient(indirect)meta-analysis indicated robotics to be favorable in terms of conversion(RR≈0.41)and severe morbidity(RR≈0.81),with a trend toward lower overall morbidity(RR≈0.92)and no difference in 30-day mortality.Differences in length of stay and operative time were small and heterogeneous.Economic evidence(indirect,network meta-analysis)suggested higher procedural costs for robotic vs laparoscopic intervention,but lower hospitalization costs vs open intervention,with laparoscopy the least expensive overall.AMSTAR 2 ratings were moderate-to-high across the reviews,GRADE certainty was low for key donor continuous outcomes,and low-to-moderate for recipient and economic outcomes.Overlap was slight(graded-corpus CCA=0.0%;including a contextual non-transplant review increased CCA to≈1.25%).CONCLUSION Robotic donor hepatectomy confers perioperative advantages at the cost of longer operative time.Recipient and economic findings are indirect and considered hypothesis-generating.Transplant-specific,prospective comparisons using a minimum standardized dataset and uniform outcome definitions are needed to resolve remaining uncertainties and to clarify the cost-utility correlation.展开更多
BACKGROUND Early renal artery thrombosis after kidney transplantation is rare but often leads to graft loss.Prompt diagnosis and intervention are essential,particularly in patients with inherited thrombophilias such a...BACKGROUND Early renal artery thrombosis after kidney transplantation is rare but often leads to graft loss.Prompt diagnosis and intervention are essential,particularly in patients with inherited thrombophilias such as factor V Leiden(FVL)mutation.CASE SUMMARY A kidney transplant recipient with FVL mutation developed an acute transplant renal artery thrombosis.The immediate post-operative Doppler ultrasonography revealed thrombosis of the main and inferior polar renal arteries.Emergent thrombectomy and separate arterial re-anastomoses were performed after cold perfusion with heparinized saline and vasodilator solution.Reperfusion was successful with immediate urine output and gradual improvement in renal function.The patient was discharged on direct oral anticoagulation therapy.CONCLUSION Early detection and surgical intervention can preserve graft function in posttransplant renal artery thrombosis even in patients at high risk.展开更多
BACKGROUND Living donor kidney transplantation is the optimal method of long-term renal replacement therapy.Minimally invasive donor nephrectomy techniques,such as robot-assisted(RALDN)and hand-assisted(HALDN)laparosc...BACKGROUND Living donor kidney transplantation is the optimal method of long-term renal replacement therapy.Minimally invasive donor nephrectomy techniques,such as robot-assisted(RALDN)and hand-assisted(HALDN)laparoscopic procedures,are well-established in high-income countries and are being increasingly adopted worldwide.Nevertheless,no studies have reported surgical outcomes of RALDN donor nephrectomy from a United Kingdom center to date.AIM To compare surgical outcomes between RALDN and HALDN laparoscopic donor nephrectomy in a United Kingdom high-volume living kidney donor transplant program.METHODS A case-control matching analysis was performed based on the following parameters:Sex,age,body mass index,procedure laterality,number of renal arteries,and previous abdominal surgeries.Key surgical outcomes,including primary warm ischemia time,operative duration,and post-operative recovery,were evaluated.RESULTS In this cohort of 140 living donors(70 RALDN vs 70 HALDN),donor and recipient outcomes were equivalent across key metrics:Pain scores,overall complication rates,readmissions,reoperations,and creatinine levels at 30 days and 1 year.Recipient long-term renal function did not differ between groups.Operative time for RALDN decreased significantly over the study period,indicating progressive improvement along the learning curve.Although RALDN was associated with a modestly longer mean warm ischaemia time(3.53 minutes vs 2.76 minutes,P<0.001)and extended hospital stay(4.21 days vs 3.17 days,P<0.001),these did not translate into any disadvantage in clinical outcomes.CONCLUSION In this first United Kingdom comparative cohort,RALDN demonstrated excellent safety and efficacy,even in the early phase of our programme,matching the outcomes of the well-established,gold-standard HALDN approach.Moreover,the pronounced learning-curve trajectory suggests considerable potential for further improvements in robotic surgical outcomes as the programme matures.展开更多
BACKGROUND With the increasing use of laparoscopic techniques in living-donor kidney transplantation,limitations in donor vessel length,particularly of the right renal vein,pose significant challenges for vascular ana...BACKGROUND With the increasing use of laparoscopic techniques in living-donor kidney transplantation,limitations in donor vessel length,particularly of the right renal vein,pose significant challenges for vascular anastomosis to the recipient’s external iliac vein.These anatomical constraints can complicate graft implantation and increase the risk of postoperative complications.CASE SUMMARY To address the issue of short right renal veins,several surgical strategies have been proposed.In this report,we describe our experience with three cases in which venous extension was successfully achieved using a venous cuff interposition technique during back-table reconstruction.This approach was used to facilitate secure vascular anastomosis and improve graft positioning in anatomically complex transplant scenarios.CONCLUSION Venous cuff interposition represents an effective technique for managing short renal veins in living-donor kidney transplantation.It provides additional length and flexibility,easing anastomotic tension and supporting successful transplantation.展开更多
基金funded by Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS),Faculty of Engineering and IT,University of Technology Sydney.Moreover,Ongoing Research Funding Program(ORF-2025-14)King Saud University,Riyadh,Saudi Arabia,under Project ORF-2025-。
文摘Face liveness detection is essential for securing biometric authentication systems against spoofing attacks,including printed photos,replay videos,and 3D masks.This study systematically evaluates pre-trained CNN models—DenseNet201,VGG16,InceptionV3,ResNet50,VGG19,MobileNetV2,Xception,and InceptionResNetV2—leveraging transfer learning and fine-tuning to enhance liveness detection performance.The models were trained and tested on NUAA and Replay-Attack datasets,with cross-dataset generalization validated on SiW-MV2 to assess real-world adaptability.Performance was evaluated using accuracy,precision,recall,FAR,FRR,HTER,and specialized spoof detection metrics(APCER,NPCER,ACER).Fine-tuning significantly improved detection accuracy,with DenseNet201 achieving the highest performance(98.5%on NUAA,97.71%on Replay-Attack),while MobileNetV2 proved the most efficient model for real-time applications(latency:15 ms,memory usage:45 MB,energy consumption:30 mJ).A statistical significance analysis(paired t-tests,confidence intervals)validated these improvements.Cross-dataset experiments identified DenseNet201 and MobileNetV2 as the most generalizable architectures,with DenseNet201 achieving 86.4%accuracy on Replay-Attack when trained on NUAA,demonstrating robust feature extraction and adaptability.In contrast,ResNet50 showed lower generalization capabilities,struggling with dataset variability and complex spoofing attacks.These findings suggest that MobileNetV2 is well-suited for low-power applications,while DenseNet201 is ideal for high-security environments requiring superior accuracy.This research provides a framework for improving real-time face liveness detection,enhancing biometric security,and guiding future advancements in AI-driven anti-spoofing techniques.
文摘Fingerprint-spoofing attack often occurs when imposters gain access illegally by using artificial fingerprints,which are made of common fingerprint materials,such as silicon,latex,etc.Thus,to protect our privacy,many fingerprint liveness detection methods are put forward to discriminate fake or true fingerprint.Current work on liveness detection for fingerprint images is focused on the construction of complex handcrafted features,but these methods normally destroy or lose spatial information between pixels.Different from existing methods,convolutional neural network(CNN)can generate high-level semantic representations by learning and concatenating low-level edge and shape features from a large amount of labeled data.Thus,CNN is explored to solve the above problem and discriminate true fingerprints from fake ones in this paper.To reduce the redundant information and extract the most distinct features,ROI and PCA operations are performed for learned features of convolutional layer or pooling layer.After that,the extracted features are fed into SVM classifier.Experimental results based on the LivDet(2013)and the LivDet(2011)datasets,which are captured by using different fingerprint materials,indicate that the classification performance of our proposed method is both efficient and convenient compared with the other previous methods.
基金supported by the NSFC (U1536206,61232016,U1405254,61373133, 61502242)BK20150925the PAPD fund
文摘Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artificial fingerprints can trick the fingerprint authentication system and access information using real users' identification.Therefore,a fingerprint liveness detection algorithm needs to be designed to prevent illegal users from accessing privacy information.In this paper,a new software-based liveness detection approach using multi-scale local phase quantity(LPQ) and principal component analysis(PCA) is proposed.The feature vectors of a fingerprint are constructed through multi-scale LPQ.PCA technology is also introduced to reduce the dimensionality of the feature vectors and gain more effective features.Finally,a training model is gained using support vector machine classifier,and the liveness of a fingerprint is detected on the basis of the training model.Experimental results demonstrate that our proposed method can detect the liveness of users' fingerprints and achieve high recognition accuracy.This study also confirms that multi-resolution analysis is a useful method for texture feature extraction during fingerprint liveness detection.
基金This work was supported in part by project supported by National Natural Science Foundation of China(Grant No.61572182,No.61370225)project supported by Hunan Provincial Natural Science Foundation of China(Grant No.15JJ2007).
文摘Aim to countermeasure the presentation attack for iris recognition system,an iris liveness detection scheme based on batch normalized convolutional neural network(BNCNN)is proposed to improve the reliability of the iris authentication system.The BNCNN architecture with eighteen layers is constructed to detect the genuine iris and fake iris,including convolutional layer,batch-normalized(BN)layer,Relu layer,pooling layer and full connected layer.The iris image is first preprocessed by iris segmentation and is normalized to 256×256 pixels,and then the iris features are extracted by BNCNN.With these features,the genuine iris and fake iris are determined by the decision-making layer.Batch normalization technique is used in BNCNN to avoid the problem of over fitting and gradient disappearing during training.Extensive experiments are conducted on three classical databases:the CASIA Iris Lamp database,the CASIA Iris Syn database and Ndcontact database.The results show that the proposed method can effectively extract micro texture features of the iris,and achieve higher detection accuracy compared with some typical iris liveness detection methods.
基金supported by theResearchers Supporting Project No.RSP-2021/14,King Saud University,Riyadh,Saudi Arabia.
文摘Contactless verification is possible with iris biometric identification,which helps prevent infections like COVID-19 from spreading.Biometric systems have grown unsteady and dangerous as a result of spoofing assaults employing contact lenses,replayed the video,and print attacks.The work demonstrates an iris liveness detection approach by utilizing fragmental coefficients of Haar transformed Iris images as signatures to prevent spoofing attacks for the very first time in the identification of iris liveness.Seven assorted feature creation ways are studied in the presented solutions,and these created features are explored for the training of eight distinct machine learning classifiers and ensembles.The predicted iris liveness identification variants are evaluated using recall,F-measure,precision,accuracy,APCER,BPCER,and ACER.Three standard datasets were used in the investigation.The main contribution of our study is achieving a good accuracy of 99.18%with a smaller feature vector.The fragmental coefficients of Haar transformed iris image of size 8∗8 utilizing random forest algorithm showed superior iris liveness detection with reduced featured vector size(64 features).Random forest gave 99.18%accuracy.Additionally,conduct an extensive experiment on cross datasets for detailed analysis.The results of our experiments showthat the iris biometric template is decreased in size tomake the proposed framework suitable for algorithmic verification in real-time environments and settings.
基金supported in part by the Public Technology Research Plan of Zhejiang Province (LGJ21F030001)the National Natural Science Foundation of China (62302448)the Zhejiang Provincial Key Laboratory of New Network Standards and Technologies (2013E10012)。
文摘In this paper, we study the supervisory control problem of discrete event systems assuming that cyber-attacks might occur. In particular, we focus on the problem of liveness enforcement and consider a sensor-reading modification attack(SM-attack) that may disguise the occurrence of an event as that of another event by intruding sensor communication channels. To solve the problem, we introduce non-deterministic supervisors in the paper, which associate to every observed sequence a set of possible control actions offline and choose a control action from the set randomly online to control the system. Specifically, given a bounded Petri net(PN) as the reference formalism and an SMattack, an algorithm that synthesizes a liveness-enforcing nondeterministic supervisor tolerant to the SM-attack is proposed for the first time.
基金the Project of Industrial Internet and Integration of Industrialization and Industrialization of Guangxi,China under Grant No.Guigong2021-37.
文摘This paper deals with the supervisory control problem of discrete event systems modeled by labeled Petri nets. The system is originally unbounded. First, the solvability of the problem is confirmed. A necessary condition is given and proven for the existence of a feasible priority-based controller based on the notions of liveness and transition invariants. Next, a cyclic behavior graph is constructed, which shows the reachable markings that guarantee the maximum liveness of the system within a given bound vector. Finally, an on-line control strategy is proposed to enforce boundedness and liveness to the given system by appending priority relations to transitions. The dynamic priority relation changes flexibly according to the current state of the system and enforces the system evolving in a bounded and live manner. In addition, numerical examples are studied to verify the validity of the proposed approach that remains the structure of the plant net and is efficient for on-line control.
文摘The probabilities for the technology to be spoofed are widely acknowledged in biometric verification system. Important efforts have been conducted to study such threats and to develop countermeasures to direct attacks to the biometric verification system to ensure the security of these systems against spoof attacks and reduce this risk, by using another module that is added to the biometric verification system called the “liveness detection” which uses different anatomical properties to distinguish between real and fake traits. Thus, the robustness of the system against direct attacks can be improved through increasing the security level offered to the final user. This paper is an attempt to construct support biometric security system to protect the iris biometric verification system from spoof attacks, through integrating the iris verification system with addition module called liveness detection which composed of two sub-modules (static and dynamic). A test has been performed, for iris verification phase performed on two types of database (MMU DB) for 180 samples and (CASIA DB) for 90 samples, and gave accuracy (99.44%) with FAR of (0.0277) and FRR (0.0055) for MMU DB, and accuracy (97.77%) with FAR of (0.0333) and FRR (0.0222) for CASIA DB.
基金supported by the National Natural Science Foundation of China(61172176)
文摘Multi-living agent system （MLAS） is a new concept in the field of complex system research, which is peculiarly suitable for the design and analysis of a complex information system in a serious confrontation and tight constraint environment. However, the universal method to quantitatively measure the living degree of an MLAS remains uncertain, which is critical to the self-organizing process. Therefore, a novel analytic hierarchy process （AHP） based method with dependent pairwise comparison matrix （PCM） for the evaluation of living degree of the MLAS is proposed, which eliminates the shortcoming of fixed PCM in traditional process. Furthermore, to avoid the annoying procedure of the consistency validation, the PCMs are appropriately reconstructed. Through an illustration of the netted radar system, the calculation detail is explicitly presented. Altogether, the advanced evaluation method successfully accomplishes the preset objective and promotes the development of the MLAS theory and AHP as well.
文摘This paper proposes an approach to making livehess model checking problems under fairness feasible.The proposed method divides such a problem into smaller ones that can be conquered.It is not superior to existing tools dedicated to model checking liveness properties under fairness assumptions in terms of model checking performance but has the following positive aspects:1)the approach can be used to model check liveness properties under anti-fairness assumptions as well as fairness assumptions,2)the approach can help humans better understand the reason why they need to use fairness and/or anti-fairness assumptions,and 3)the approach makes it possible to use existing linear temporal logic model checkers to model check liveness properties under fairness and/or anti-fairness assumptions.
文摘Several liveness theorems for GFC (the generalized free choice) systems in a reductive approach are presented.What is interesting is that the characterization is just based on deadlocks,rather than on both deadlocks and traps as Commoner characterizes the liveness of ordinary free-choice systems.Several proof techniques which may be useful for proving liveness of other types of net systems are also introduced.
文摘The significant features concerning liveness of generalized free-choice (GFC) systems are discussed.These features provide a sound basis for analyzing liveness of GFC systems in a reductive approach.What is interesting is that the characterization is just based on deadlocks,rather than on both deadlocks and traps as Commoner characterizes the liveness of ordinary free-choice systems.Several proof techniques for proving liveness-related features of GFC systems are introduced.
基金the National Natural Science Foundation of China (No.60073013) and the NKBRSF of China (No.G1998030416).
文摘In this paper, the Extended Strong Asymmetric Choice Nets Ⅱ (ESACN Ⅱ), a subclass of Asymmetric Choice Nets (ACN) including Extended Free Choice Nets (EFCN) and Strong Asymmetric Choke Nets Ⅱ (SACN Ⅱ, is presented. A necessary and sufficient condition for liveness of ESACN Ⅱ is proposed. Moreover, a criterion is introduced, which is necessary and sufficient for judgement of liveness and boundedness of ESACN Ⅱ. Meanwhile a polynomial time algorithm is given to decide liveness and boundedness for ESACN Ⅱ.
文摘BACKGROUND Robotic assistance is increasingly used for donor and recipient hepatectomy in liver transplantation,yet existing evidence is fragmented and variably indirect.AIM To evaluate clinical outcomes,surgical performance,and economic effects of robotic-assisted donor and recipient hepatectomy in the transplant pathway.METHODS Following Preferred Reporting Items for Systematic reviews and Meta-Analyses 2020 and a priori registration,systematic reviews were included with or without meta-analysis.Four databases were searched through July 2025.Methodological quality was appraised with a measurement tool to assess systematic reviews(AMSTAR 2),and certainty was graded with grading of recommendations assessment,development and evaluation(GRADE).Evidence overlap was calculated via a citation-matrix-based corrected covered area(CCA).Effect sizes were prespecified as risk ratios(RR)for dichotomous outcomes and mean differences for continuous outcomes.RESULTS Five reviews met the inclusion criteria,four with meta-analyses and one consensus review used only for context.Donor(direct)findings were more favorable for robotics in terms of estimated blood loss(≈-117 mL)and length of stay(≈-0.6 days),although with longer operative time(≈+105 minutes).Absolute risks for donor complications were not estimable from ratio-only data.Recipient(indirect)meta-analysis indicated robotics to be favorable in terms of conversion(RR≈0.41)and severe morbidity(RR≈0.81),with a trend toward lower overall morbidity(RR≈0.92)and no difference in 30-day mortality.Differences in length of stay and operative time were small and heterogeneous.Economic evidence(indirect,network meta-analysis)suggested higher procedural costs for robotic vs laparoscopic intervention,but lower hospitalization costs vs open intervention,with laparoscopy the least expensive overall.AMSTAR 2 ratings were moderate-to-high across the reviews,GRADE certainty was low for key donor continuous outcomes,and low-to-moderate for recipient and economic outcomes.Overlap was slight(graded-corpus CCA=0.0%;including a contextual non-transplant review increased CCA to≈1.25%).CONCLUSION Robotic donor hepatectomy confers perioperative advantages at the cost of longer operative time.Recipient and economic findings are indirect and considered hypothesis-generating.Transplant-specific,prospective comparisons using a minimum standardized dataset and uniform outcome definitions are needed to resolve remaining uncertainties and to clarify the cost-utility correlation.
文摘BACKGROUND Early renal artery thrombosis after kidney transplantation is rare but often leads to graft loss.Prompt diagnosis and intervention are essential,particularly in patients with inherited thrombophilias such as factor V Leiden(FVL)mutation.CASE SUMMARY A kidney transplant recipient with FVL mutation developed an acute transplant renal artery thrombosis.The immediate post-operative Doppler ultrasonography revealed thrombosis of the main and inferior polar renal arteries.Emergent thrombectomy and separate arterial re-anastomoses were performed after cold perfusion with heparinized saline and vasodilator solution.Reperfusion was successful with immediate urine output and gradual improvement in renal function.The patient was discharged on direct oral anticoagulation therapy.CONCLUSION Early detection and surgical intervention can preserve graft function in posttransplant renal artery thrombosis even in patients at high risk.
文摘BACKGROUND Living donor kidney transplantation is the optimal method of long-term renal replacement therapy.Minimally invasive donor nephrectomy techniques,such as robot-assisted(RALDN)and hand-assisted(HALDN)laparoscopic procedures,are well-established in high-income countries and are being increasingly adopted worldwide.Nevertheless,no studies have reported surgical outcomes of RALDN donor nephrectomy from a United Kingdom center to date.AIM To compare surgical outcomes between RALDN and HALDN laparoscopic donor nephrectomy in a United Kingdom high-volume living kidney donor transplant program.METHODS A case-control matching analysis was performed based on the following parameters:Sex,age,body mass index,procedure laterality,number of renal arteries,and previous abdominal surgeries.Key surgical outcomes,including primary warm ischemia time,operative duration,and post-operative recovery,were evaluated.RESULTS In this cohort of 140 living donors(70 RALDN vs 70 HALDN),donor and recipient outcomes were equivalent across key metrics:Pain scores,overall complication rates,readmissions,reoperations,and creatinine levels at 30 days and 1 year.Recipient long-term renal function did not differ between groups.Operative time for RALDN decreased significantly over the study period,indicating progressive improvement along the learning curve.Although RALDN was associated with a modestly longer mean warm ischaemia time(3.53 minutes vs 2.76 minutes,P<0.001)and extended hospital stay(4.21 days vs 3.17 days,P<0.001),these did not translate into any disadvantage in clinical outcomes.CONCLUSION In this first United Kingdom comparative cohort,RALDN demonstrated excellent safety and efficacy,even in the early phase of our programme,matching the outcomes of the well-established,gold-standard HALDN approach.Moreover,the pronounced learning-curve trajectory suggests considerable potential for further improvements in robotic surgical outcomes as the programme matures.
文摘BACKGROUND With the increasing use of laparoscopic techniques in living-donor kidney transplantation,limitations in donor vessel length,particularly of the right renal vein,pose significant challenges for vascular anastomosis to the recipient’s external iliac vein.These anatomical constraints can complicate graft implantation and increase the risk of postoperative complications.CASE SUMMARY To address the issue of short right renal veins,several surgical strategies have been proposed.In this report,we describe our experience with three cases in which venous extension was successfully achieved using a venous cuff interposition technique during back-table reconstruction.This approach was used to facilitate secure vascular anastomosis and improve graft positioning in anatomically complex transplant scenarios.CONCLUSION Venous cuff interposition represents an effective technique for managing short renal veins in living-donor kidney transplantation.It provides additional length and flexibility,easing anastomotic tension and supporting successful transplantation.
