In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by re...In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.展开更多
Next-generation 6G networks seek to provide ultra-reliable and low-latency communications,necessitating network designs that are intelligent and adaptable.Network slicing has developed as an effective option for resou...Next-generation 6G networks seek to provide ultra-reliable and low-latency communications,necessitating network designs that are intelligent and adaptable.Network slicing has developed as an effective option for resource separation and service-level differentiation inside virtualized infrastructures.Nonetheless,sustaining elevated Quality of Service(QoS)in dynamic,resource-limited systems poses significant hurdles.This study introduces an innovative packet-based proactive end-to-end(ETE)resource management system that facilitates network slicing with improved resilience and proactivity.To get around the drawbacks of conventional reactive systems,we develop a cost-efficient slice provisioning architecture that takes into account limits on radio,processing,and transmission resources.The optimization issue is non-convex,NP-hard,and requires online resolution in a dynamic setting.We offer a hybrid solution that integrates an advanced Deep Reinforcement Learning(DRL)methodology with an Improved Manta-Ray Foraging Optimization(ImpMRFO)algorithm.The ImpMRFO utilizes Chebyshev chaotic mapping for the formation of a varied starting population and incorporates Lévy flight-based stochastic movement to avert premature convergence,hence facilitating improved exploration-exploitation trade-offs.The DRL model perpetually acquires optimum provisioning strategies via agent-environment interactions,whereas the ImpMRFO enhances policy performance for effective slice provisioning.The solution,developed in Python,is evaluated across several 6G slicing scenarios that include varied QoS profiles and traffic requirements.The DRL model perpetually acquires optimum provisioning methods via agent-environment interactions,while the ImpMRFO enhances policy performance for effective slice provisioning.The solution,developed in Python,is evaluated across several 6G slicing scenarios that include varied QoS profiles and traffic requirements.Experimental findings reveal that the proactive ETE system outperforms DRL models and non-resilient provisioning techniques.Our technique increases PSSRr,decreases average latency,and optimizes resource use.These results demonstrate that the hybrid architecture for robust,real-time,and scalable slice management in future 6G networks is feasible.展开更多
DDoS attacks represent one of the most pervasive and evolving threats in cybersecurity,capable of crippling critical infrastructures and disrupting services globally.As networks continue to expand and threats become m...DDoS attacks represent one of the most pervasive and evolving threats in cybersecurity,capable of crippling critical infrastructures and disrupting services globally.As networks continue to expand and threats become more sophisticated,there is an urgent need for Intrusion Detection Systems(IDS)capable of handling these challenges effectively.Traditional IDS models frequently have difficulties in detecting new or changing attack patterns since they heavily depend on existing characteristics.This paper presents a novel approach for detecting unknown Distributed Denial of Service(DDoS)attacks by integrating Sliced Iterative Normalizing Flows(SINF)into IDS.SINF utilizes the Sliced Wasserstein distance to repeatedly modify probability distributions,enabling better management of high-dimensional data when there are only a few samples available.The unique architecture of SINF ensures efficient density estimation and robust sample generation,enabling IDS to adapt dynamically to emerging threats without relying heavily on predefined signatures or extensive retraining.By incorporating Open-Set Recognition(OSR)techniques,this method improves the system’s ability to detect both known and unknown attacks while maintaining high detection performance.The experimental evaluation on CICIDS2017 and CICDDoS2019 datasets demonstrates that the proposed system achieves an accuracy of 99.85%for known attacks and an F1 score of 99.99%after incremental learning for unknown attacks.The results clearly demonstrate the system’s strong generalization capability across unseen attacks while maintaining the computational efficiency required for real-world deployment.展开更多
Multi-layer slopes are widely found in clay residue receiving fields.A generalized horizontal slice method(GHSM)for assessing the stability of multi-layer slopes that considers the energy dissipation between adjacent ...Multi-layer slopes are widely found in clay residue receiving fields.A generalized horizontal slice method(GHSM)for assessing the stability of multi-layer slopes that considers the energy dissipation between adjacent horizontal slices is presented.In view of the upper-bound limit analysis theory,the energy equation is derived and the ultimate failure mode is generated by comparing the sliding surface passing through the slope toe(mode A)with that below(mode B).In addition,the influence of the number of slices on the stability coefficients in the GHSM is studied and the stable value is obtained.Compared to the original method(Chen’s method),the GHSM can acquire more precise results,which takes into account the energy dissipation in the inner sliding soil mass.Moreover,the GHSM,limit equilibrium method(LEM)and numerical simulation method(NSM)are applied to analyze the stability of a multi-layer slope with different slope angles and the results of the safety factor and failure mode are very close in each case.The ultimate failure modes are shown to be mode B when the slope angle is not more than 28°.It illustrates that the determination of the ultimate sliding surface requires comparison of multiple failure modes,not only mode A.展开更多
Objective: To investigate the effect of ginger slice acupoint application combined with moxibustion on chemotherapy-induced vomiting in postoperative breast cancer patients. Methods: Sixty postoperative breast cancer ...Objective: To investigate the effect of ginger slice acupoint application combined with moxibustion on chemotherapy-induced vomiting in postoperative breast cancer patients. Methods: Sixty postoperative breast cancer patients undergoing chemotherapy were randomly divided into an observation group and a control group, with 30 patients in each group. The control group received antiemetic treatment with dolasetron, while the observation group received ginger slice acupoint application combined with moxibustion in addition to antiemetic treatment to address chemotherapy-induced vomiting. The vomiting response on days 1-3 was compared between the two groups, along with R-INVR retching scores and patient satisfaction with the intervention methods. Results: On days 2 and 3 of chemotherapy, the observation group showed significantly less vomiting than the control group, with differences reaching a highly significant level (P < 0.001). On day 3, the R-INVR score in the observation group was significantly lower than that of the control group, with a highly significant difference (P < 0.001). The satisfaction score in the observation group was 8.38 ± 0.81, higher than the control group’s 7.65 ± 0.71, with a statistically significant difference (P < 0.05). Conclusion: Ginger slice acupoint application combined with moxibustion effectively alleviates chemotherapy-induced vomiting in postoperative breast cancer patients, improves quality of life, and is worth promoting clinically.展开更多
In the 5th generation(5G)wireless communication networks,network slicing emerges where network operators(NPs)form isolated logical slices by the same cellular network infrastructure and spectrum resource.In coverage r...In the 5th generation(5G)wireless communication networks,network slicing emerges where network operators(NPs)form isolated logical slices by the same cellular network infrastructure and spectrum resource.In coverage regions of access points(APs)shared by slices,device to device(D2D)communication can occur among different slices,i.e.,one device acts as D2D relay for another device serving by a different slice,which is defined as slice cooperation in this paper.Since selfish slices will not help other slices by cooperation voluntarily and unconditionally,this paper designs a novel resource allocation scheme to stimulate slice cooperation.The main idea is to encourage slice to perform cooperation for other slices by rewarding it with higher throughput.The proposed incentive scheme for slice cooperation is formulated by an optimal problem,where cooperative activities are introduced to the objective function.Since optimal solutions of the formulated problem are long term statistics,though can be obtained,a practical online slice scheduling algorithm is designed,which can obtain optimal solutions of the formulated maximal problem.Lastly,the throughput isolation indexes are defined to evaluate isolation performance of slice.According to simulation results,the proposed incentive scheme for slice cooperation can stimulate slice cooperation effectively,and the isolation of slice is also simulated and discussed.展开更多
This paper suggests that a single class rather than methods should be used as the slice scope to compute class cohesion. First, for a given attribute, the statements in all methods that last define the attribute are c...This paper suggests that a single class rather than methods should be used as the slice scope to compute class cohesion. First, for a given attribute, the statements in all methods that last define the attribute are computed. Then, the forward and backward data slices for this attribute are generated by using the class as the slice scope and are combined to compute the corresponding class data slice. Finally, the class cohesion is computed based on all class data slices for the attributes. Compared to traditional cohesion metrics that use methods as the slice scope, the proposed metrics that use a single class as slice scope take into account the possible interactions between the methods. The experimental results show that class cohesion can be more accurately measured when using the class as the slice scope.展开更多
Although slice methods are simple and effective slope stability analysis approaches,they are statically indeterminate.Several modifications of the slice method,such as the Spencer,MorgensternPrice,and Chen-Morgenstern...Although slice methods are simple and effective slope stability analysis approaches,they are statically indeterminate.Several modifications of the slice method,such as the Spencer,MorgensternPrice,and Chen-Morgenstern methods,are statically determinate and solvable as they assume the inter-slice force inclination angle;however,there is a small gap between the assumptions and actual landslide stability analysis.Through reasonable theoretical analysis,the Su slice method provides a reliable approach for determining the inter-slice force inclination angle that can be used in slice analysis to accurately analyse,calculate,and evaluate the stability of landslides.However,the Su slice method requires further research and analysis,especially in terms of the parameter values sinλbiandρ.In this study,we investigated more accurate methods for calculating the parameters sinλbiandρ.In addition,an adjustment coefficient(μ)was introduced to improve the solution method for the inter-slice force inclination angle.The inter-slice force inclination and safety factors of three landslides with arc-shaped slip surfaces and one landslide with a polyline-shaped slip surface were analysed and compared using the different slice methods.The improved inter-slice force inclination not only satisfies the calculation of static force equilibrium condition but also satisfies the calculation of both the force and moment equilibrium conditions.The improved method for calculating inter-slice force inclination presented the best correlation.The safety factors calculated using the improved Su slice method were close to those obtained using numerical simulations and the Morgenstern-Price method.Despite negligible differences among the safety factors calculated using the Su slice,improved Su slice,and M-P methods,the accuracy of the improved Su slice method was better than the M-P method in terms of inter-slice force inclination angles which can be useful to improve protection engineering design.展开更多
To improve the accuracy and speed in cycle-accurate power estimation, this paper uses multiple dimensional coefficients to build a Bayesian inference dynamic power model. By analyzing the power distribution and intern...To improve the accuracy and speed in cycle-accurate power estimation, this paper uses multiple dimensional coefficients to build a Bayesian inference dynamic power model. By analyzing the power distribution and internal node state, we find the deficiency of only using port information. Then, we define the gate level number computing method and the concept of slice, and propose using slice analysis to distill switching density as coefficients in a special circuit stage and participate in Bayesian inference with port information. Experiments show that this method can reduce the power-per-cycle estimation error by 21.9% and the root mean square error by 25.0% compared with the original model, and maintain a 700 ＋ speedup compared with the existing gate-level power analysis technique.展开更多
[Objective] The aim was to investigate the effects of different drying temperatures on the physiochemical properties and antioxidant activity of balsam pear slices. [Method] Balsam pear slices were dried at different ...[Objective] The aim was to investigate the effects of different drying temperatures on the physiochemical properties and antioxidant activity of balsam pear slices. [Method] Balsam pear slices were dried at different hot air temperatures, 40, 50, 60, 70 and 80 ℃. [Result] The polyphenols content was highest （2.83 mg/g） in the balsam pear slices dried at 50 ℃, and the flavonoids content was highest （2.584 mg/g） in those dried at 60 ℃. Different drying temperatures had a great impact on the antioxidant capacity of polyphenols in balsam pear. The balsam pear slices dried at 50 ℃ showed the strongest capacity for scavenging DPPH free radicals with IC50 of 0.015 mg/ml, and those dried at 80 ℃ showed the strongest capacity for removing ABTS free radicals with IC50 of 0.0689 mg/ml. [Conclusion] The hot air temperature of 50 ℃ had the least impact on the quality of balsam pear slices.展开更多
5G use cases,for example enhanced mobile broadband(eMBB),massive machine-type communications(mMTC),and an ultra-reliable low latency communication(URLLC),need a network architecture capable of sustaining stringent lat...5G use cases,for example enhanced mobile broadband(eMBB),massive machine-type communications(mMTC),and an ultra-reliable low latency communication(URLLC),need a network architecture capable of sustaining stringent latency and bandwidth requirements;thus,it should be extremely flexible and dynamic.Slicing enables service providers to develop various network slice architectures.As users travel from one coverage region to another area,the callmust be routed to a slice thatmeets the same or different expectations.This research aims to develop and evaluate an algorithm to make handover decisions appearing in 5G sliced networks.Rules of thumb which indicates the accuracy regarding the training data classification schemes within machine learning should be considered for validation and selection of the appropriate machine learning strategies.Therefore,this study discusses the network model’s design and implementation of self-optimization Fuzzy Qlearning of the decision-making algorithm for slice handover.The algorithm’s performance is assessed by means of connection-level metrics considering the Quality of Service(QoS),specifically the probability of the new call to be blocked and the probability of a handoff call being dropped.Hence,within the network model,the call admission control(AC)method is modeled by leveraging supervised learning algorithm as prior knowledge of additional capacity.Moreover,to mitigate high complexity,the integration of fuzzy logic as well as Fuzzy Q-Learning is used to discretize state and the corresponding action spaces.The results generated from our proposal surpass the traditional methods without the use of supervised learning and fuzzy-Q learning.展开更多
The functions studied in the paper are the quaternion-valued functions of a quaternionic variable.It is shown that the left slice regular functions and right slice regular functions are related by a particular involut...The functions studied in the paper are the quaternion-valued functions of a quaternionic variable.It is shown that the left slice regular functions and right slice regular functions are related by a particular involution,and that the intrinsic slice regular functions play a central role in the theory of slice regular functions.The relation between left slice regular functions,right slice regular functions and intrinsic slice regular functions is revealed.As an application,the classical Laplace transform is generalized naturally to quaternions in two different ways,which transform a quaternion-valued function of a real variable to a left or right slice regular function.The usual properties of the classical Laplace transforms are generalized to quaternionic Laplace transforms.展开更多
This paper presents a new closure to slice models for evaluating slopes. The discussion is based on the minimal inter-slice action (MIA) hypothesis, which results in a new slice model without including artificially ad...This paper presents a new closure to slice models for evaluating slopes. The discussion is based on the minimal inter-slice action (MIA) hypothesis, which results in a new slice model without including artificially adjustable parameters. It has been realized that the new slice model predicts the minimum value of the safety factor, while all other slice models available always overestimate the value of the safety factor. Moreover, the gravity moment of each slice is found to be opposite to the overturning moment, which is different from the existing knowledge. In particular, the new slice model overcomes the situation where different assumptions of the inter-slice force function will give different safety factors to the same slope. The related numerical examples indicate that the new slice model can serve as a reliable tool for investigating geotechnical slope stability.展开更多
文摘In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.
文摘Next-generation 6G networks seek to provide ultra-reliable and low-latency communications,necessitating network designs that are intelligent and adaptable.Network slicing has developed as an effective option for resource separation and service-level differentiation inside virtualized infrastructures.Nonetheless,sustaining elevated Quality of Service(QoS)in dynamic,resource-limited systems poses significant hurdles.This study introduces an innovative packet-based proactive end-to-end(ETE)resource management system that facilitates network slicing with improved resilience and proactivity.To get around the drawbacks of conventional reactive systems,we develop a cost-efficient slice provisioning architecture that takes into account limits on radio,processing,and transmission resources.The optimization issue is non-convex,NP-hard,and requires online resolution in a dynamic setting.We offer a hybrid solution that integrates an advanced Deep Reinforcement Learning(DRL)methodology with an Improved Manta-Ray Foraging Optimization(ImpMRFO)algorithm.The ImpMRFO utilizes Chebyshev chaotic mapping for the formation of a varied starting population and incorporates Lévy flight-based stochastic movement to avert premature convergence,hence facilitating improved exploration-exploitation trade-offs.The DRL model perpetually acquires optimum provisioning strategies via agent-environment interactions,whereas the ImpMRFO enhances policy performance for effective slice provisioning.The solution,developed in Python,is evaluated across several 6G slicing scenarios that include varied QoS profiles and traffic requirements.The DRL model perpetually acquires optimum provisioning methods via agent-environment interactions,while the ImpMRFO enhances policy performance for effective slice provisioning.The solution,developed in Python,is evaluated across several 6G slicing scenarios that include varied QoS profiles and traffic requirements.Experimental findings reveal that the proactive ETE system outperforms DRL models and non-resilient provisioning techniques.Our technique increases PSSRr,decreases average latency,and optimizes resource use.These results demonstrate that the hybrid architecture for robust,real-time,and scalable slice management in future 6G networks is feasible.
基金supported by the National Science and Technology Council,Taiwan with grant numbers NSTC 112-2221-E-992-045,112-2221-E-992-057-MY3,and 112-2622-8-992-009-TD1.
文摘DDoS attacks represent one of the most pervasive and evolving threats in cybersecurity,capable of crippling critical infrastructures and disrupting services globally.As networks continue to expand and threats become more sophisticated,there is an urgent need for Intrusion Detection Systems(IDS)capable of handling these challenges effectively.Traditional IDS models frequently have difficulties in detecting new or changing attack patterns since they heavily depend on existing characteristics.This paper presents a novel approach for detecting unknown Distributed Denial of Service(DDoS)attacks by integrating Sliced Iterative Normalizing Flows(SINF)into IDS.SINF utilizes the Sliced Wasserstein distance to repeatedly modify probability distributions,enabling better management of high-dimensional data when there are only a few samples available.The unique architecture of SINF ensures efficient density estimation and robust sample generation,enabling IDS to adapt dynamically to emerging threats without relying heavily on predefined signatures or extensive retraining.By incorporating Open-Set Recognition(OSR)techniques,this method improves the system’s ability to detect both known and unknown attacks while maintaining high detection performance.The experimental evaluation on CICIDS2017 and CICDDoS2019 datasets demonstrates that the proposed system achieves an accuracy of 99.85%for known attacks and an F1 score of 99.99%after incremental learning for unknown attacks.The results clearly demonstrate the system’s strong generalization capability across unseen attacks while maintaining the computational efficiency required for real-world deployment.
基金support provided by the National Key R&D Program of China(No.2017YFC1501304)the National Natural Science Foundation of China(Nos.42090054,41922055 and 41931295)the Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)(No.CUGGC09).
文摘Multi-layer slopes are widely found in clay residue receiving fields.A generalized horizontal slice method(GHSM)for assessing the stability of multi-layer slopes that considers the energy dissipation between adjacent horizontal slices is presented.In view of the upper-bound limit analysis theory,the energy equation is derived and the ultimate failure mode is generated by comparing the sliding surface passing through the slope toe(mode A)with that below(mode B).In addition,the influence of the number of slices on the stability coefficients in the GHSM is studied and the stable value is obtained.Compared to the original method(Chen’s method),the GHSM can acquire more precise results,which takes into account the energy dissipation in the inner sliding soil mass.Moreover,the GHSM,limit equilibrium method(LEM)and numerical simulation method(NSM)are applied to analyze the stability of a multi-layer slope with different slope angles and the results of the safety factor and failure mode are very close in each case.The ultimate failure modes are shown to be mode B when the slope angle is not more than 28°.It illustrates that the determination of the ultimate sliding surface requires comparison of multiple failure modes,not only mode A.
文摘Objective: To investigate the effect of ginger slice acupoint application combined with moxibustion on chemotherapy-induced vomiting in postoperative breast cancer patients. Methods: Sixty postoperative breast cancer patients undergoing chemotherapy were randomly divided into an observation group and a control group, with 30 patients in each group. The control group received antiemetic treatment with dolasetron, while the observation group received ginger slice acupoint application combined with moxibustion in addition to antiemetic treatment to address chemotherapy-induced vomiting. The vomiting response on days 1-3 was compared between the two groups, along with R-INVR retching scores and patient satisfaction with the intervention methods. Results: On days 2 and 3 of chemotherapy, the observation group showed significantly less vomiting than the control group, with differences reaching a highly significant level (P < 0.001). On day 3, the R-INVR score in the observation group was significantly lower than that of the control group, with a highly significant difference (P < 0.001). The satisfaction score in the observation group was 8.38 ± 0.81, higher than the control group’s 7.65 ± 0.71, with a statistically significant difference (P < 0.05). Conclusion: Ginger slice acupoint application combined with moxibustion effectively alleviates chemotherapy-induced vomiting in postoperative breast cancer patients, improves quality of life, and is worth promoting clinically.
基金supported by Beijing Natural Science Foundation under Grant number L172049the National Science and CAS Engineering Laboratory for Intelligent Agricultural Machinery Equipment GC201907-02
文摘In the 5th generation(5G)wireless communication networks,network slicing emerges where network operators(NPs)form isolated logical slices by the same cellular network infrastructure and spectrum resource.In coverage regions of access points(APs)shared by slices,device to device(D2D)communication can occur among different slices,i.e.,one device acts as D2D relay for another device serving by a different slice,which is defined as slice cooperation in this paper.Since selfish slices will not help other slices by cooperation voluntarily and unconditionally,this paper designs a novel resource allocation scheme to stimulate slice cooperation.The main idea is to encourage slice to perform cooperation for other slices by rewarding it with higher throughput.The proposed incentive scheme for slice cooperation is formulated by an optimal problem,where cooperative activities are introduced to the objective function.Since optimal solutions of the formulated problem are long term statistics,though can be obtained,a practical online slice scheduling algorithm is designed,which can obtain optimal solutions of the formulated maximal problem.Lastly,the throughput isolation indexes are defined to evaluate isolation performance of slice.According to simulation results,the proposed incentive scheme for slice cooperation can stimulate slice cooperation effectively,and the isolation of slice is also simulated and discussed.
基金The National Natural Science Foundation of China(No.60425206,60633010)the High Technology Research and Development Program of Jiangsu Province(No.BG2005032)
文摘This paper suggests that a single class rather than methods should be used as the slice scope to compute class cohesion. First, for a given attribute, the statements in all methods that last define the attribute are computed. Then, the forward and backward data slices for this attribute are generated by using the class as the slice scope and are combined to compute the corresponding class data slice. Finally, the class cohesion is computed based on all class data slices for the attributes. Compared to traditional cohesion metrics that use methods as the slice scope, the proposed metrics that use a single class as slice scope take into account the possible interactions between the methods. The experimental results show that class cohesion can be more accurately measured when using the class as the slice scope.
基金evolution mechanism and prevention countermeasures of the Outang landslide in the Three Gorges Reservoir Area(No.20C0023)research projectthe geological safety risk investigation,evaluation and control of key resettlement towns in the Three Gorges Reservoir Area(No.HBHDZFCG2021025)+2 种基金the National Natural Science Foundation of China(No.42077268)the Chongqing Geological Disaster Prevention and Control Center of China(No.20C0023)the open fund of state key laboratory of geohazard prevention and geoenvironment protection(No.SKLGP2020K015)。
文摘Although slice methods are simple and effective slope stability analysis approaches,they are statically indeterminate.Several modifications of the slice method,such as the Spencer,MorgensternPrice,and Chen-Morgenstern methods,are statically determinate and solvable as they assume the inter-slice force inclination angle;however,there is a small gap between the assumptions and actual landslide stability analysis.Through reasonable theoretical analysis,the Su slice method provides a reliable approach for determining the inter-slice force inclination angle that can be used in slice analysis to accurately analyse,calculate,and evaluate the stability of landslides.However,the Su slice method requires further research and analysis,especially in terms of the parameter values sinλbiandρ.In this study,we investigated more accurate methods for calculating the parameters sinλbiandρ.In addition,an adjustment coefficient(μ)was introduced to improve the solution method for the inter-slice force inclination angle.The inter-slice force inclination and safety factors of three landslides with arc-shaped slip surfaces and one landslide with a polyline-shaped slip surface were analysed and compared using the different slice methods.The improved inter-slice force inclination not only satisfies the calculation of static force equilibrium condition but also satisfies the calculation of both the force and moment equilibrium conditions.The improved method for calculating inter-slice force inclination presented the best correlation.The safety factors calculated using the improved Su slice method were close to those obtained using numerical simulations and the Morgenstern-Price method.Despite negligible differences among the safety factors calculated using the Su slice,improved Su slice,and M-P methods,the accuracy of the improved Su slice method was better than the M-P method in terms of inter-slice force inclination angles which can be useful to improve protection engineering design.
文摘To improve the accuracy and speed in cycle-accurate power estimation, this paper uses multiple dimensional coefficients to build a Bayesian inference dynamic power model. By analyzing the power distribution and internal node state, we find the deficiency of only using port information. Then, we define the gate level number computing method and the concept of slice, and propose using slice analysis to distill switching density as coefficients in a special circuit stage and participate in Bayesian inference with port information. Experiments show that this method can reduce the power-per-cycle estimation error by 21.9% and the root mean square error by 25.0% compared with the original model, and maintain a 700 ＋ speedup compared with the existing gate-level power analysis technique.
文摘[Objective] The aim was to investigate the effects of different drying temperatures on the physiochemical properties and antioxidant activity of balsam pear slices. [Method] Balsam pear slices were dried at different hot air temperatures, 40, 50, 60, 70 and 80 ℃. [Result] The polyphenols content was highest （2.83 mg/g） in the balsam pear slices dried at 50 ℃, and the flavonoids content was highest （2.584 mg/g） in those dried at 60 ℃. Different drying temperatures had a great impact on the antioxidant capacity of polyphenols in balsam pear. The balsam pear slices dried at 50 ℃ showed the strongest capacity for scavenging DPPH free radicals with IC50 of 0.015 mg/ml, and those dried at 80 ℃ showed the strongest capacity for removing ABTS free radicals with IC50 of 0.0689 mg/ml. [Conclusion] The hot air temperature of 50 ℃ had the least impact on the quality of balsam pear slices.
基金This work was supported partially by the BK21 FOUR program of the National Research Foundation of Korea funded by the Ministry of Education(NRF5199991514504)by theMSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2023-2018-0-01431)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation).
文摘5G use cases,for example enhanced mobile broadband(eMBB),massive machine-type communications(mMTC),and an ultra-reliable low latency communication(URLLC),need a network architecture capable of sustaining stringent latency and bandwidth requirements;thus,it should be extremely flexible and dynamic.Slicing enables service providers to develop various network slice architectures.As users travel from one coverage region to another area,the callmust be routed to a slice thatmeets the same or different expectations.This research aims to develop and evaluate an algorithm to make handover decisions appearing in 5G sliced networks.Rules of thumb which indicates the accuracy regarding the training data classification schemes within machine learning should be considered for validation and selection of the appropriate machine learning strategies.Therefore,this study discusses the network model’s design and implementation of self-optimization Fuzzy Qlearning of the decision-making algorithm for slice handover.The algorithm’s performance is assessed by means of connection-level metrics considering the Quality of Service(QoS),specifically the probability of the new call to be blocked and the probability of a handoff call being dropped.Hence,within the network model,the call admission control(AC)method is modeled by leveraging supervised learning algorithm as prior knowledge of additional capacity.Moreover,to mitigate high complexity,the integration of fuzzy logic as well as Fuzzy Q-Learning is used to discretize state and the corresponding action spaces.The results generated from our proposal surpass the traditional methods without the use of supervised learning and fuzzy-Q learning.
基金supported by NSFC(12071422)Zhejiang Province Science Foundation of China(LY14A010018)。
文摘The functions studied in the paper are the quaternion-valued functions of a quaternionic variable.It is shown that the left slice regular functions and right slice regular functions are related by a particular involution,and that the intrinsic slice regular functions play a central role in the theory of slice regular functions.The relation between left slice regular functions,right slice regular functions and intrinsic slice regular functions is revealed.As an application,the classical Laplace transform is generalized naturally to quaternions in two different ways,which transform a quaternion-valued function of a real variable to a left or right slice regular function.The usual properties of the classical Laplace transforms are generalized to quaternionic Laplace transforms.
文摘This paper presents a new closure to slice models for evaluating slopes. The discussion is based on the minimal inter-slice action (MIA) hypothesis, which results in a new slice model without including artificially adjustable parameters. It has been realized that the new slice model predicts the minimum value of the safety factor, while all other slice models available always overestimate the value of the safety factor. Moreover, the gravity moment of each slice is found to be opposite to the overturning moment, which is different from the existing knowledge. In particular, the new slice model overcomes the situation where different assumptions of the inter-slice force function will give different safety factors to the same slope. The related numerical examples indicate that the new slice model can serve as a reliable tool for investigating geotechnical slope stability.
