Image processing networks have gained great success in many fields,and thus the issue of copyright protection for image processing networks hasbecome a focus of attention. Model watermarking techniques are widely used...Image processing networks have gained great success in many fields,and thus the issue of copyright protection for image processing networks hasbecome a focus of attention. Model watermarking techniques are widely usedin model copyright protection, but there are two challenges: (1) designinguniversal trigger sample watermarking for different network models is stilla challenge;(2) existing methods of copyright protection based on trigger swatermarking are difficult to resist forgery attacks. In this work, we propose adual model watermarking framework for copyright protection in image processingnetworks. The trigger sample watermark is embedded in the trainingprocess of the model, which can effectively verify the model copyright. And wedesign a common method for generating trigger sample watermarks based ongenerative adversarial networks, adaptively generating trigger sample watermarksaccording to different models. The spatial watermark is embedded intothe model output. When an attacker steals model copyright using a forgedtrigger sample watermark, which can be correctly extracted to distinguishbetween the piratical and the protected model. The experiments show that theproposed framework has good performance in different image segmentationnetworks of UNET, UNET++, and FCN (fully convolutional network), andeffectively resists forgery attacks.展开更多
In the real world, the inputs of many complicated systems are time-varying functions or processes. In order to predict the outputs of these systems with high speed and accuracy, this paper proposes a time series predi...In the real world, the inputs of many complicated systems are time-varying functions or processes. In order to predict the outputs of these systems with high speed and accuracy, this paper proposes a time series prediction model based on the wavelet process neural network, and develops the corresponding learning algorithm based on the expansion of the orthogonal basis functions. The effectiveness of the proposed time series prediction model and its learning algorithm is proved by the Macke-Glass time series prediction, and the comparative prediction results indicate that the proposed time series prediction model based on the wavelet process neural network seems to perform well and appears suitable for using as a good tool to predict the highly complex nonlinear time series.展开更多
The air transportation network, one of the common multilayer complex systems, is composed of a collection of individual airlines, and each airline corresponds to a different layer. An important question is then how ma...The air transportation network, one of the common multilayer complex systems, is composed of a collection of individual airlines, and each airline corresponds to a different layer. An important question is then how many airlines are really necessary to represent the optimal structure of a multilayer air transportation system. Here we take the Chinese air transportation network (CATN) as an example to explore the nature of multiplex systems through the procedure of network aggregation. Specifically, we propose a series of structural measures to characterize the CATN from the multilayered to the aggregated network level. We show how these measures evolve during the network aggregation process in which layers are gradually merged together and find that there is an evident structural transition that happened in the aggregated network with nine randomly chosen airlines merged, where the network features and construction cost of this network are almost equivalent to those of the present CATN with twenty-two airlines under this condition. These findings could shed some light on network structure optimization and management of the Chinese air transportation system.展开更多
Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsu...Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsum, cement, lime and water glass were used as adhesive, and the strength of different material ratios were investigated in this study. The influence factors of clay strength were obtained in the order of cement, gypsum, water glass and lime. The results show that the cement content is the determinant influence factor, and gypsum has positive effects, while the water glass can enhance both clay strength and the fluidity of the filing slurry. Furthermore, combining chaotic optimization method with neural network, the optimal ratio of composite cementing agent was obtained. The results show that the optimal ratio of water glass, cement, lime and clay (in quality) is 1.17:6.74:4.17:87.92 in the process of bottom self-flow filling, while the optimal ratio is 1.78:9.58:4.71:83.93 for roof-contacted filling. A novel filling process to fill in gypsum mine goaf with clay is established. The engineering practice shows that the filling cost is low, thus, notable economic benefit is achieved.展开更多
The controller in software-defined networking(SDN)acts as strategic point of control for the underlying network.Multiple controllers are available,and every single controller retains a number of features such as the O...The controller in software-defined networking(SDN)acts as strategic point of control for the underlying network.Multiple controllers are available,and every single controller retains a number of features such as the OpenFlow version,clustering,modularity,platform,and partnership support,etc.They are regarded as vital when making a selection among a set of controllers.As such,the selection of the controller becomes a multi-criteria decision making(MCDM)problem with several features.Hence,an increase in this number will increase the computational complexity of the controller selection process.Previously,the selection of controllers based on features has been studied by the researchers.However,the prioritization of features has gotten less attention.Moreover,several features increase the computational complexity of the selection process.In this paper,we propose a mathematical modeling for feature prioritization with analytical network process(ANP)bridge model for SDN controllers.The results indicate that a prioritized features model lead to a reduction in the computational complexity of the selection of SDN controller.In addition,our model generates prioritized features for SDN controllers.展开更多
The employment of natural fibres in fused deposition modeling has raised much attention from researchers in finding a suitable formulation for the natural fibre composite filaments.Moreover,selection of suitable natur...The employment of natural fibres in fused deposition modeling has raised much attention from researchers in finding a suitable formulation for the natural fibre composite filaments.Moreover,selection of suitable natural fibres for fused deposition modeling should be performed before the development of the composites.It could not be performed without identifying selection criteria that comprehend both materials and fused deposition modeling process requirements.Therefore,in this study,integration of the Analytic Hierarchy Process(AHP)/Analytic Network Process(ANP)has been introduced in selecting the natural fibres based in different clusters of selection concurrently.The selection process has been performed based on the interdependency among the selection criteria.Pairwise comparison matrices are constructed based on AHP’s hierarchical model and super matrices are constructed based on the ANP’s network model.As a result,flax fibre has ranked at the top of the selection by scored 19.5%from the overall evaluation.Flax fibre has excellent material properties and been found in various natural fibre composite applications.Further investigation is needed to study the compatibility of this fibre to be reinforced with a thermoplastic polymer matrix to develop a resultant natural fibre composite filament for fused deposition modeling.展开更多
The dynamic characteristic of complex network failure and recovery is one of the main research topics in complex networks. Real world systems such as traffic jams and Internet recovery could be described by the comple...The dynamic characteristic of complex network failure and recovery is one of the main research topics in complex networks. Real world systems such as traffic jams and Internet recovery could be described by the complex network theory. We propose a model to study the recovery process in complex networks. Two different recovery mechanisms are considered in three kinds of networks: external recovery and internal recovery. By simulating the process of the nodes recovery in networks, it is found that the system exhibits the feature of first-order phase transition only when the external recovery is considered. Internal recovery cannot induce such a kind of transitions. As external recovery and internal recovery coexist on networks, the systems will retain the most efficient part of external recovery and internal recovery. Meanwhile, a hysteresis could be observed when increasing or decreasing the failure probability. Finally, a largest degree node protection strategy is proposed for improving the robustness of networks.展开更多
Three recent breakthroughs due to AI in arts and science serve as motivation:An award winning digital image,protein folding,fast matrix multiplication.Many recent developments in artificial neural networks,particularl...Three recent breakthroughs due to AI in arts and science serve as motivation:An award winning digital image,protein folding,fast matrix multiplication.Many recent developments in artificial neural networks,particularly deep learning(DL),applied and relevant to computational mechanics(solid,fluids,finite-element technology)are reviewed in detail.Both hybrid and pure machine learning(ML)methods are discussed.Hybrid methods combine traditional PDE discretizations with ML methods either(1)to help model complex nonlinear constitutive relations,(2)to nonlinearly reduce the model order for efficient simulation(turbulence),or(3)to accelerate the simulation by predicting certain components in the traditional integration methods.Here,methods(1)and(2)relied on Long-Short-Term Memory(LSTM)architecture,with method(3)relying on convolutional neural networks.Pure ML methods to solve(nonlinear)PDEs are represented by Physics-Informed Neural network(PINN)methods,which could be combined with attention mechanism to address discontinuous solutions.Both LSTM and attention architectures,together with modern and generalized classic optimizers to include stochasticity for DL networks,are extensively reviewed.Kernel machines,including Gaussian processes,are provided to sufficient depth for more advanced works such as shallow networks with infinite width.Not only addressing experts,readers are assumed familiar with computational mechanics,but not with DL,whose concepts and applications are built up from the basics,aiming at bringing first-time learners quickly to the forefront of research.History and limitations of AI are recounted and discussed,with particular attention at pointing out misstatements or misconceptions of the classics,even in well-known references.Positioning and pointing control of a large-deformable beam is given as an example.展开更多
Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional...Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional time-varying algorithm limits prediction accuracy, thus affecting a number of operational decisions. To solve this problem, a time-varying auto regressive (TVAR) model based on the process neural network (PNN) and the empirical mode decomposition (EMD) is proposed. The time-varying system is tracked on-line by establishing a time-varying parameter model, and then the relevant parameter spectrum is obtained. Firstly, the EMD method is utilized to decompose the signal into several intrinsic mode functions (IMFs). Then for each IMF, the PNN is established and the time-varying auto-spectral density is obtained. Finally, the time-frequency distribution of the signals can be reconstructed by linear superposition. The simulation and the analytical results from an example demonstrate that this approach possesses simplicity, effectiveness, and feasibility, as well as higher frequency resolution.展开更多
Hazards and disasters have always negative impacts on the way of life.Landslide is an overwhelming natural as well as man-made disaster that causes loss of natural resources and human properties throughout theworld.Th...Hazards and disasters have always negative impacts on the way of life.Landslide is an overwhelming natural as well as man-made disaster that causes loss of natural resources and human properties throughout theworld.The present study aimed to assess and compare the prediction efficiency of different models in landslide susceptibility in the Kysuca river basin,Slovakia.In this regard,the fuzzy decision-making trial and evaluation laboratory combining with the analytic network process(FDEMATEL-ANP),Naïve Bayes(NB)classifier,and random forest(RF)classifier were considered.Initially,a landslide inventory map was produced with 2000 landslide and nonlandslide points by randomly dividedwith a ratio of 70%:30%for training and testing,respectively.The geospatial database for assessing the landslide susceptibility was generated with the help of 16 landslide conditioning factors by allowing for topographical,hydrological,lithological,and land cover factors.The ReliefF methodwas considered for determining the significance of selected conditioning factors and inclusion in the model building.Consequently,the landslide susceptibility maps(LSMs)were generated using the FDEMATEL-ANP,Naïve Bayes(NB)classifier,and random forest(RF)classifier models.Finally,the area under curve(AUC)and different arithmetic evaluation were used for validating and comparing the results and models.The results revealed that random forest(RF)classifier is a promising and optimum model for landslide susceptibility in the study area with a very high value of area under curve(AUC=0.954),lower value of mean absolute error(MAE=0.1238)and root mean square error(RMSE=0.2555),and higher value of Kappa index(K=0.8435)and overall accuracy(OAC=92.2%).展开更多
This study developed specific criteria and a fuzzy analytic network process(FANP)to assess and select portfolios on the Tehran Stock Exchange(TSE).Although the portfolio selection problem has been widely investigated,...This study developed specific criteria and a fuzzy analytic network process(FANP)to assess and select portfolios on the Tehran Stock Exchange(TSE).Although the portfolio selection problem has been widely investigated,most studies have focused on income and risk as the main decision-making criteria.However,there are many other important criteria that have been neglected.To fill this gap,first,a literature review was conducted to determine the main criteria for portfolio selection,and a Likert-type questionnaire was then used to finalize a list of criteria.Second,the finalized criteria were applied in an FANP to rank 10 different TSE portfolios.The results indicated that profitability,growth,market,and risk are the most important criteria for portfolio selection.Additionally,portfolios 6,7,2,4,8,1,5,3,9,and 10(A6,A7,A2,A4,A8,A1,A5,A3,A9,and A10)were found to be the best choices.Implications and directions for future research are discussed.展开更多
Bloom filter(BF)is a space-and-time efficient probabilistic technique that helps answermembership queries.However,BF faces several issues.The problems with traditional BF are generally two.Firstly,a large number of fa...Bloom filter(BF)is a space-and-time efficient probabilistic technique that helps answermembership queries.However,BF faces several issues.The problems with traditional BF are generally two.Firstly,a large number of false positives can return wrong content when the data is queried.Secondly,the large size of BF is a bottleneck in the speed of querying and thus uses large memory.In order to solve the above two issues,in this article,we propose the check bits concept.From the implementation perspective,in the check bits approach,before saving the content value in the BF,we obtain the binary representation of the content value.Then,we take some bits of the content value,we call these the check bits.These bits are stored in a separate array such that they point to the same location as the BF.Finally,the content value(data)is stored in the BF based on the hash function values.Before retrieval of data from BF,the reverse process of the steps ensures that even if the same hash functions output has been generated for the content,the check bits make sure that the retrieval does not depend on the hash output alone.This thus helps in the reduction of false positives.In the experimental evaluation,we are able to reduce more than 50%of false positives.In our proposed approach,the false positives can still occur,however,false positives can only occur if the hash functions and check bits generate the same value for a particular content.The chances of such scenarios are less,therefore,we get a reduction of approximately more than 50%false positives in all cases.We believe that the proposed approach adds to the state of the art and opens new directions as such.展开更多
A study was conducted to select the best alternative for the development of construction panels as well as investment in its manufacturing in Iran.Three alternatives are considered,cement-bonded wood composite product...A study was conducted to select the best alternative for the development of construction panels as well as investment in its manufacturing in Iran.Three alternatives are considered,cement-bonded wood composite product,substituted products(such as concrete panel) sandwich panel and a mixture of them.We apply the analytic network process(ANP) to achieve this goal.A hierarchy is designed to prioritize benefits,opportunities,costs and risks(BOCR) by using the Analytic Hierarchy Process(AHP) ratings approach.To evaluate the "control criteria" of the system,a control hierarchy is also created and prioritized by applying the Analytic Network Process(ANP).A total of four major control criteria in the system are prioritized where each one controls a decision network evaluated using ANP.The final synthesis of the system shows cement-bonded wood composite product is the best choice among three potential alternatives for the investment and development.展开更多
The current cyber-attack environment has put even the most protected systems at risk as the hackers are nowmodifying technologies to exploit even the tiniest of weaknesses and infiltrate networks.In this situation,it...The current cyber-attack environment has put even the most protected systems at risk as the hackers are nowmodifying technologies to exploit even the tiniest of weaknesses and infiltrate networks.In this situation,it’s critical to design and construct software that is both secure and long-lasting.While security is the most well-defined aspect of health information software systems,it is equally significant to prioritise sustainability because any health information software system will be more effective if it provides both security and sustainability to the customers at the same time.In this league,it is crucial to determine those characteristics in the systems that can help in the accurate assessment of the sustainable-security of the health information software during the development stage.This research work employed the Fuzzy Analytic Network Process(Fuzzy ANP)to estimate the impact of the overall sustainable-security of health information software systems and their characteristics in order to achieve a high level of sustainable-security.Furthermore,the study validates the efficacy of the Fuzzy ANP procedure by testing it on five different versions of a health information software system through Fuzzy Technique for Order of Preference by Similarity to Ideal Solutions(Fuzzy TOPSIS).Despite the sensitivity of the health information software systems,this study employedmultiple versions of health information software system.When compared with the existing procedures for testing the sustainable-security of health information software systems,the outcomes were conclusive and significantly more effective.Besides saving time and resources,the mechanism suggested in this research work aims to establish an outline that software practitioners can follow to enhance the sustainablesecurity of health information software systems.展开更多
The advantages of a cloud computing service are cost advantages,availability,scalability,flexibility,reduced time to market,and dynamic access to computing resources.Enterprises can improve the successful adoption rate...The advantages of a cloud computing service are cost advantages,availability,scalability,flexibility,reduced time to market,and dynamic access to computing resources.Enterprises can improve the successful adoption rate of cloud computing services if they understand the critical factors.Tofind critical factors,this studyfirst reviewed the literature and established a three-layer hierarch-ical factor table for adopting a cloud computing service based on the Technology-Organization-Environment framework.Then,a hybrid method that combines two multi-criteria decision-making tools—called the Fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical factors for the adop-tion of a cloud computing service,replacing the subjective decision of the authors.The results of this study determinedfive critical factors,namely data access secur-ity,information transmission security,senior management support,fallback cloud management,and employee acceptance.Finally,the paper presents thefindings and implications of the study.展开更多
Land suitability assessment (LSA) is an essential step in the process of determining environmental limits for sustainable crop production. Up to date, studies on LSA for crop production in Cameroon have been based on ...Land suitability assessment (LSA) is an essential step in the process of determining environmental limits for sustainable crop production. Up to date, studies on LSA for crop production in Cameroon have been based on empirical methods which are limited as they consider similar singnificance levels for all evaluation criteria and do not consider the interrelationships of criteria in the best-fit models. In the present study a qualitative land suitability evaluation by an integrated multi-criteria decision-making (MCDM) approach and geographic information system (GIS) was tested to assess and map suitable land units for maize (Zea mays L) production in Cameroon Western highland. Eight environmental criteria identified as the most relevant for maize production in the area of interest (AOI) saw their thematic maps prepared using ArcGIS 10.8. The relationship between criteria was considered by the DEMATEL method. The criteria were weighted using the ANP method. Thereafter, the land suitability map was obtained using the weighted overlay analysis (WOA) in ArcGIS. The results obtained indicated that slope has the highest specific weight and consequently the greatest influence on land suitability for maize production in the locality. The land suitability map generated showed that Foumbot’s agricultural land suitability for maize production varies from very high to marginally suitable (99% of the surface area). Specifically, 11% (8056 ha) is very highly suitable, 29% (21,119 ha) is highly suitable, 38% (27,405 ha) are moderately suitable and 20% (14,422 ha) are marginally suitable. The remaining 1% that falls under non suitable class represents 606 ha and is located on the steep slopes around the Mount Mbappit. The kappa analysis reveals a total overall accuracy of 78.67% and a kappa value of 0.7256 with an asymptotic error of 0.058 which is good. Then the model used in this research is highly recommended for future land evaluation works in Cameroon and similar ecosystems around the world.展开更多
This paper proposes a framework for evaluating the efficacy and suitability of maintenance programs with a focus on quantitative risk assessment in the domain of aircraft maintenance task transfer. The analysis is anc...This paper proposes a framework for evaluating the efficacy and suitability of maintenance programs with a focus on quantitative risk assessment in the domain of aircraft maintenance task transfer. The analysis is anchored in the principles of Maintenance Steering Group-3 (MSG-3) logic decision paradigms. The paper advances a holistic risk assessment index architecture tailored for the task transfer of maintenance programs. Utilizing the analytic network process (ANP), the study quantifies the weight interrelationships among diverse variables, incorporating expert-elicited subjective weighting. A multielement connection number-based evaluative model is employed to characterize decision-specific data, thereby facilitating the quantification of task transfer-associated risk through the appraisal of set-pair potentials. Moreover, the paper conducts a temporal risk trend analysis founded on partial connection numbers of varying orders. This analytical construct serves to streamline the process of risk assessment pertinent to maintenance program task transfer. The empirical component of this research, exemplified through a case study of the Boeing 737NG aircraft maintenance program, corroborates the methodological robustness and pragmatic applicability of the proposed framework in the quantification and analysis of mission transfer risk.展开更多
The Analytic Network Process (ANP) is a multicriteria theory of measurement used to derive relative priority scales of absolute numbers from individual judgments (or from actual measurements normalized to a relative f...The Analytic Network Process (ANP) is a multicriteria theory of measurement used to derive relative priority scales of absolute numbers from individual judgments (or from actual measurements normalized to a relative form) that also belong to a fundamental scale of absolute numbers. These judgments represent the relative influence, of one of two elements over the other in a pairwise comparison process on a third element in the system, with respect to an underlying control criterion. Through its supermatrix, whose entries are themselves matrices of column priorities, the ANP synthesizes the outcome of dependence and feedback within and between clusters of elements. The Analytic Hierarchy Process (AHP) with its independence assumptions on upper levels from lower levels and the independence of the elements in a level is a special case of the ANP. The ANP is an essential tool for articulating our understanding of a decision problem. One had to overcome the limitation of linear hierarchic structures and their mathematical consequences. This part on the ANP summarizes and illustrates the basic concepts of the ANP and shows how informed intuitive judgments can lead to real life answers that are matched by actual measurements in the real world (for example, relative dollar values) as illustrated in market share examples that rely on judgments and not on numerical data.展开更多
This is the first part of an introduction to multicriteria decision making using the Analytic Hierarchy Process (AHP) and its generalization, the Analytic Network Process (ANP). The discussion involves individual and ...This is the first part of an introduction to multicriteria decision making using the Analytic Hierarchy Process (AHP) and its generalization, the Analytic Network Process (ANP). The discussion involves individual and group decisions both with the independence of the criteria from the alternatives as in the AHP and also with dependence and feedback in the entire decision structure as in the ANP. This part explains the Analytic Hierarchy Process, with examples, and presents in some detail the mathematical foundations. An exposition of the Analytic Network Process and its applications will appear in later issues of this journal.展开更多
The general theory of the ANP enables one to deal with the benefits,opportunities,costs,andrisks(the BOCR merits)of a decision,by introducing the notion of negative priorites for C and Ralong with the rating(not compa...The general theory of the ANP enables one to deal with the benefits,opportunities,costs,andrisks(the BOCR merits)of a decision,by introducing the notion of negative priorites for C and Ralong with the rating(not comparison)of the top priority alternative synthesized for each of the fourmerits in terms of strategic criteria to enable one to combine the four B,O,C,and R values of eachalternative into a single outcome.Strategic criteria are very basic criteria individuals and groups useto assess whether they should make any of the many decisions they face in their daily operations.They do not depend on any particular decision for their priorities but are assessed in terms of the goalsand values of the individual or organization.Synthesis is made with two formulas,one multiplicativeand one additive subtractive that can give rise to negative overall priorities.This paper summarizesand illustrates basic complex decisions involving several control criteria under each of the BOCRmerits.展开更多
基金supported by the National Natural Science Foundation of China under grants U1836208,by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)fundby the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET)fund,China.
文摘Image processing networks have gained great success in many fields,and thus the issue of copyright protection for image processing networks hasbecome a focus of attention. Model watermarking techniques are widely usedin model copyright protection, but there are two challenges: (1) designinguniversal trigger sample watermarking for different network models is stilla challenge;(2) existing methods of copyright protection based on trigger swatermarking are difficult to resist forgery attacks. In this work, we propose adual model watermarking framework for copyright protection in image processingnetworks. The trigger sample watermark is embedded in the trainingprocess of the model, which can effectively verify the model copyright. And wedesign a common method for generating trigger sample watermarks based ongenerative adversarial networks, adaptively generating trigger sample watermarksaccording to different models. The spatial watermark is embedded intothe model output. When an attacker steals model copyright using a forgedtrigger sample watermark, which can be correctly extracted to distinguishbetween the piratical and the protected model. The experiments show that theproposed framework has good performance in different image segmentationnetworks of UNET, UNET++, and FCN (fully convolutional network), andeffectively resists forgery attacks.
基金Project supported by the National Natural Science Foundation of China (Grant No 60572174)the Doctoral Fund of Ministry of Education of China (Grant No 20070213072)+2 种基金the 111 Project (Grant No B07018)the China Postdoctoral Science Foundation (Grant No 20070410264)the Development Program for Outstanding Young Teachers in Harbin Institute of Technology (Grant No HITQNJS.2007.010)
文摘In the real world, the inputs of many complicated systems are time-varying functions or processes. In order to predict the outputs of these systems with high speed and accuracy, this paper proposes a time series prediction model based on the wavelet process neural network, and develops the corresponding learning algorithm based on the expansion of the orthogonal basis functions. The effectiveness of the proposed time series prediction model and its learning algorithm is proved by the Macke-Glass time series prediction, and the comparative prediction results indicate that the proposed time series prediction model based on the wavelet process neural network seems to perform well and appears suitable for using as a good tool to predict the highly complex nonlinear time series.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11405118,11401448 and 11301403
文摘The air transportation network, one of the common multilayer complex systems, is composed of a collection of individual airlines, and each airline corresponds to a different layer. An important question is then how many airlines are really necessary to represent the optimal structure of a multilayer air transportation system. Here we take the Chinese air transportation network (CATN) as an example to explore the nature of multiplex systems through the procedure of network aggregation. Specifically, we propose a series of structural measures to characterize the CATN from the multilayered to the aggregated network level. We show how these measures evolve during the network aggregation process in which layers are gradually merged together and find that there is an evident structural transition that happened in the aggregated network with nine randomly chosen airlines merged, where the network features and construction cost of this network are almost equivalent to those of the present CATN with twenty-two airlines under this condition. These findings could shed some light on network structure optimization and management of the Chinese air transportation system.
基金supported by the National Basic Research and Development Program of China (No. 2010CB732004)the joint funding of the National Natural Science Foundation and Shanghai Baosteel Group Corporation of China (No. 51074177)
文摘Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsum, cement, lime and water glass were used as adhesive, and the strength of different material ratios were investigated in this study. The influence factors of clay strength were obtained in the order of cement, gypsum, water glass and lime. The results show that the cement content is the determinant influence factor, and gypsum has positive effects, while the water glass can enhance both clay strength and the fluidity of the filing slurry. Furthermore, combining chaotic optimization method with neural network, the optimal ratio of composite cementing agent was obtained. The results show that the optimal ratio of water glass, cement, lime and clay (in quality) is 1.17:6.74:4.17:87.92 in the process of bottom self-flow filling, while the optimal ratio is 1.78:9.58:4.71:83.93 for roof-contacted filling. A novel filling process to fill in gypsum mine goaf with clay is established. The engineering practice shows that the filling cost is low, thus, notable economic benefit is achieved.
基金This research was supported partially by LIG Nex1It was also supported partially by the MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2021-2018-0-01431)supervised by the IITP(Institute for Information&Communications Technology Planning Evaluation).
文摘The controller in software-defined networking(SDN)acts as strategic point of control for the underlying network.Multiple controllers are available,and every single controller retains a number of features such as the OpenFlow version,clustering,modularity,platform,and partnership support,etc.They are regarded as vital when making a selection among a set of controllers.As such,the selection of the controller becomes a multi-criteria decision making(MCDM)problem with several features.Hence,an increase in this number will increase the computational complexity of the controller selection process.Previously,the selection of controllers based on features has been studied by the researchers.However,the prioritization of features has gotten less attention.Moreover,several features increase the computational complexity of the selection process.In this paper,we propose a mathematical modeling for feature prioritization with analytical network process(ANP)bridge model for SDN controllers.The results indicate that a prioritized features model lead to a reduction in the computational complexity of the selection of SDN controller.In addition,our model generates prioritized features for SDN controllers.
基金Mastura M.T.received financial support from the Ministry of Higher Education Malaysia(https://www.mohe.gov.my/en/services/research/mygrants)Universiti Teknikal Malaysia Melaka through the Fundamental Research Grant Scheme(FRGS/1/2020/FTKMP-CARE/F00456).
文摘The employment of natural fibres in fused deposition modeling has raised much attention from researchers in finding a suitable formulation for the natural fibre composite filaments.Moreover,selection of suitable natural fibres for fused deposition modeling should be performed before the development of the composites.It could not be performed without identifying selection criteria that comprehend both materials and fused deposition modeling process requirements.Therefore,in this study,integration of the Analytic Hierarchy Process(AHP)/Analytic Network Process(ANP)has been introduced in selecting the natural fibres based in different clusters of selection concurrently.The selection process has been performed based on the interdependency among the selection criteria.Pairwise comparison matrices are constructed based on AHP’s hierarchical model and super matrices are constructed based on the ANP’s network model.As a result,flax fibre has ranked at the top of the selection by scored 19.5%from the overall evaluation.Flax fibre has excellent material properties and been found in various natural fibre composite applications.Further investigation is needed to study the compatibility of this fibre to be reinforced with a thermoplastic polymer matrix to develop a resultant natural fibre composite filament for fused deposition modeling.
基金Supported by the National Natural Science foundation of China under Grant No 11474221
文摘The dynamic characteristic of complex network failure and recovery is one of the main research topics in complex networks. Real world systems such as traffic jams and Internet recovery could be described by the complex network theory. We propose a model to study the recovery process in complex networks. Two different recovery mechanisms are considered in three kinds of networks: external recovery and internal recovery. By simulating the process of the nodes recovery in networks, it is found that the system exhibits the feature of first-order phase transition only when the external recovery is considered. Internal recovery cannot induce such a kind of transitions. As external recovery and internal recovery coexist on networks, the systems will retain the most efficient part of external recovery and internal recovery. Meanwhile, a hysteresis could be observed when increasing or decreasing the failure probability. Finally, a largest degree node protection strategy is proposed for improving the robustness of networks.
文摘Three recent breakthroughs due to AI in arts and science serve as motivation:An award winning digital image,protein folding,fast matrix multiplication.Many recent developments in artificial neural networks,particularly deep learning(DL),applied and relevant to computational mechanics(solid,fluids,finite-element technology)are reviewed in detail.Both hybrid and pure machine learning(ML)methods are discussed.Hybrid methods combine traditional PDE discretizations with ML methods either(1)to help model complex nonlinear constitutive relations,(2)to nonlinearly reduce the model order for efficient simulation(turbulence),or(3)to accelerate the simulation by predicting certain components in the traditional integration methods.Here,methods(1)and(2)relied on Long-Short-Term Memory(LSTM)architecture,with method(3)relying on convolutional neural networks.Pure ML methods to solve(nonlinear)PDEs are represented by Physics-Informed Neural network(PINN)methods,which could be combined with attention mechanism to address discontinuous solutions.Both LSTM and attention architectures,together with modern and generalized classic optimizers to include stochasticity for DL networks,are extensively reviewed.Kernel machines,including Gaussian processes,are provided to sufficient depth for more advanced works such as shallow networks with infinite width.Not only addressing experts,readers are assumed familiar with computational mechanics,but not with DL,whose concepts and applications are built up from the basics,aiming at bringing first-time learners quickly to the forefront of research.History and limitations of AI are recounted and discussed,with particular attention at pointing out misstatements or misconceptions of the classics,even in well-known references.Positioning and pointing control of a large-deformable beam is given as an example.
基金Aeronautical Science Foundation of China (20071551016)
文摘Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional time-varying algorithm limits prediction accuracy, thus affecting a number of operational decisions. To solve this problem, a time-varying auto regressive (TVAR) model based on the process neural network (PNN) and the empirical mode decomposition (EMD) is proposed. The time-varying system is tracked on-line by establishing a time-varying parameter model, and then the relevant parameter spectrum is obtained. Firstly, the EMD method is utilized to decompose the signal into several intrinsic mode functions (IMFs). Then for each IMF, the PNN is established and the time-varying auto-spectral density is obtained. Finally, the time-frequency distribution of the signals can be reconstructed by linear superposition. The simulation and the analytical results from an example demonstrate that this approach possesses simplicity, effectiveness, and feasibility, as well as higher frequency resolution.
文摘Hazards and disasters have always negative impacts on the way of life.Landslide is an overwhelming natural as well as man-made disaster that causes loss of natural resources and human properties throughout theworld.The present study aimed to assess and compare the prediction efficiency of different models in landslide susceptibility in the Kysuca river basin,Slovakia.In this regard,the fuzzy decision-making trial and evaluation laboratory combining with the analytic network process(FDEMATEL-ANP),Naïve Bayes(NB)classifier,and random forest(RF)classifier were considered.Initially,a landslide inventory map was produced with 2000 landslide and nonlandslide points by randomly dividedwith a ratio of 70%:30%for training and testing,respectively.The geospatial database for assessing the landslide susceptibility was generated with the help of 16 landslide conditioning factors by allowing for topographical,hydrological,lithological,and land cover factors.The ReliefF methodwas considered for determining the significance of selected conditioning factors and inclusion in the model building.Consequently,the landslide susceptibility maps(LSMs)were generated using the FDEMATEL-ANP,Naïve Bayes(NB)classifier,and random forest(RF)classifier models.Finally,the area under curve(AUC)and different arithmetic evaluation were used for validating and comparing the results and models.The results revealed that random forest(RF)classifier is a promising and optimum model for landslide susceptibility in the study area with a very high value of area under curve(AUC=0.954),lower value of mean absolute error(MAE=0.1238)and root mean square error(RMSE=0.2555),and higher value of Kappa index(K=0.8435)and overall accuracy(OAC=92.2%).
文摘This study developed specific criteria and a fuzzy analytic network process(FANP)to assess and select portfolios on the Tehran Stock Exchange(TSE).Although the portfolio selection problem has been widely investigated,most studies have focused on income and risk as the main decision-making criteria.However,there are many other important criteria that have been neglected.To fill this gap,first,a literature review was conducted to determine the main criteria for portfolio selection,and a Likert-type questionnaire was then used to finalize a list of criteria.Second,the finalized criteria were applied in an FANP to rank 10 different TSE portfolios.The results indicated that profitability,growth,market,and risk are the most important criteria for portfolio selection.Additionally,portfolios 6,7,2,4,8,1,5,3,9,and 10(A6,A7,A2,A4,A8,A1,A5,A3,A9,and A10)were found to be the best choices.Implications and directions for future research are discussed.
基金The authors would like to thank the chair of Prince Faisal binMishaal Al Saud for Artificial Intelligent research for funding this research work through the project number QU-CPFAI-2-7-4Also would like to extend their appreciation to the Deputyship for Research&Innovation,Ministry of Education,and the Deanship of Scientific Research,Qassim University,for their support of this research.
文摘Bloom filter(BF)is a space-and-time efficient probabilistic technique that helps answermembership queries.However,BF faces several issues.The problems with traditional BF are generally two.Firstly,a large number of false positives can return wrong content when the data is queried.Secondly,the large size of BF is a bottleneck in the speed of querying and thus uses large memory.In order to solve the above two issues,in this article,we propose the check bits concept.From the implementation perspective,in the check bits approach,before saving the content value in the BF,we obtain the binary representation of the content value.Then,we take some bits of the content value,we call these the check bits.These bits are stored in a separate array such that they point to the same location as the BF.Finally,the content value(data)is stored in the BF based on the hash function values.Before retrieval of data from BF,the reverse process of the steps ensures that even if the same hash functions output has been generated for the content,the check bits make sure that the retrieval does not depend on the hash output alone.This thus helps in the reduction of false positives.In the experimental evaluation,we are able to reduce more than 50%of false positives.In our proposed approach,the false positives can still occur,however,false positives can only occur if the hash functions and check bits generate the same value for a particular content.The chances of such scenarios are less,therefore,we get a reduction of approximately more than 50%false positives in all cases.We believe that the proposed approach adds to the state of the art and opens new directions as such.
文摘A study was conducted to select the best alternative for the development of construction panels as well as investment in its manufacturing in Iran.Three alternatives are considered,cement-bonded wood composite product,substituted products(such as concrete panel) sandwich panel and a mixture of them.We apply the analytic network process(ANP) to achieve this goal.A hierarchy is designed to prioritize benefits,opportunities,costs and risks(BOCR) by using the Analytic Hierarchy Process(AHP) ratings approach.To evaluate the "control criteria" of the system,a control hierarchy is also created and prioritized by applying the Analytic Network Process(ANP).A total of four major control criteria in the system are prioritized where each one controls a decision network evaluated using ANP.The final synthesis of the system shows cement-bonded wood composite product is the best choice among three potential alternatives for the investment and development.
基金Funding for this study was received fromthe Ministry of Education and Deanship of Scientific Research at King Abdulaziz University,Kingdom of Saudi Arabia under Grant No.IFPHI-287-611-2020.
文摘The current cyber-attack environment has put even the most protected systems at risk as the hackers are nowmodifying technologies to exploit even the tiniest of weaknesses and infiltrate networks.In this situation,it’s critical to design and construct software that is both secure and long-lasting.While security is the most well-defined aspect of health information software systems,it is equally significant to prioritise sustainability because any health information software system will be more effective if it provides both security and sustainability to the customers at the same time.In this league,it is crucial to determine those characteristics in the systems that can help in the accurate assessment of the sustainable-security of the health information software during the development stage.This research work employed the Fuzzy Analytic Network Process(Fuzzy ANP)to estimate the impact of the overall sustainable-security of health information software systems and their characteristics in order to achieve a high level of sustainable-security.Furthermore,the study validates the efficacy of the Fuzzy ANP procedure by testing it on five different versions of a health information software system through Fuzzy Technique for Order of Preference by Similarity to Ideal Solutions(Fuzzy TOPSIS).Despite the sensitivity of the health information software systems,this study employedmultiple versions of health information software system.When compared with the existing procedures for testing the sustainable-security of health information software systems,the outcomes were conclusive and significantly more effective.Besides saving time and resources,the mechanism suggested in this research work aims to establish an outline that software practitioners can follow to enhance the sustainablesecurity of health information software systems.
基金supported by the Ministry of Science and Technology(MOST),Taiwan,R.O.C.(104-2410-H-327-024-).
文摘The advantages of a cloud computing service are cost advantages,availability,scalability,flexibility,reduced time to market,and dynamic access to computing resources.Enterprises can improve the successful adoption rate of cloud computing services if they understand the critical factors.Tofind critical factors,this studyfirst reviewed the literature and established a three-layer hierarch-ical factor table for adopting a cloud computing service based on the Technology-Organization-Environment framework.Then,a hybrid method that combines two multi-criteria decision-making tools—called the Fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical factors for the adop-tion of a cloud computing service,replacing the subjective decision of the authors.The results of this study determinedfive critical factors,namely data access secur-ity,information transmission security,senior management support,fallback cloud management,and employee acceptance.Finally,the paper presents thefindings and implications of the study.
文摘Land suitability assessment (LSA) is an essential step in the process of determining environmental limits for sustainable crop production. Up to date, studies on LSA for crop production in Cameroon have been based on empirical methods which are limited as they consider similar singnificance levels for all evaluation criteria and do not consider the interrelationships of criteria in the best-fit models. In the present study a qualitative land suitability evaluation by an integrated multi-criteria decision-making (MCDM) approach and geographic information system (GIS) was tested to assess and map suitable land units for maize (Zea mays L) production in Cameroon Western highland. Eight environmental criteria identified as the most relevant for maize production in the area of interest (AOI) saw their thematic maps prepared using ArcGIS 10.8. The relationship between criteria was considered by the DEMATEL method. The criteria were weighted using the ANP method. Thereafter, the land suitability map was obtained using the weighted overlay analysis (WOA) in ArcGIS. The results obtained indicated that slope has the highest specific weight and consequently the greatest influence on land suitability for maize production in the locality. The land suitability map generated showed that Foumbot’s agricultural land suitability for maize production varies from very high to marginally suitable (99% of the surface area). Specifically, 11% (8056 ha) is very highly suitable, 29% (21,119 ha) is highly suitable, 38% (27,405 ha) are moderately suitable and 20% (14,422 ha) are marginally suitable. The remaining 1% that falls under non suitable class represents 606 ha and is located on the steep slopes around the Mount Mbappit. The kappa analysis reveals a total overall accuracy of 78.67% and a kappa value of 0.7256 with an asymptotic error of 0.058 which is good. Then the model used in this research is highly recommended for future land evaluation works in Cameroon and similar ecosystems around the world.
基金supported by the Civil Aviation Administration of China(CAAC)"Safety Capability"Building Fund(Grant No.AADSA2019009)the Fundamental Research Funds of Central Universities(Grant No.3122022060).
文摘This paper proposes a framework for evaluating the efficacy and suitability of maintenance programs with a focus on quantitative risk assessment in the domain of aircraft maintenance task transfer. The analysis is anchored in the principles of Maintenance Steering Group-3 (MSG-3) logic decision paradigms. The paper advances a holistic risk assessment index architecture tailored for the task transfer of maintenance programs. Utilizing the analytic network process (ANP), the study quantifies the weight interrelationships among diverse variables, incorporating expert-elicited subjective weighting. A multielement connection number-based evaluative model is employed to characterize decision-specific data, thereby facilitating the quantification of task transfer-associated risk through the appraisal of set-pair potentials. Moreover, the paper conducts a temporal risk trend analysis founded on partial connection numbers of varying orders. This analytical construct serves to streamline the process of risk assessment pertinent to maintenance program task transfer. The empirical component of this research, exemplified through a case study of the Boeing 737NG aircraft maintenance program, corroborates the methodological robustness and pragmatic applicability of the proposed framework in the quantification and analysis of mission transfer risk.
文摘The Analytic Network Process (ANP) is a multicriteria theory of measurement used to derive relative priority scales of absolute numbers from individual judgments (or from actual measurements normalized to a relative form) that also belong to a fundamental scale of absolute numbers. These judgments represent the relative influence, of one of two elements over the other in a pairwise comparison process on a third element in the system, with respect to an underlying control criterion. Through its supermatrix, whose entries are themselves matrices of column priorities, the ANP synthesizes the outcome of dependence and feedback within and between clusters of elements. The Analytic Hierarchy Process (AHP) with its independence assumptions on upper levels from lower levels and the independence of the elements in a level is a special case of the ANP. The ANP is an essential tool for articulating our understanding of a decision problem. One had to overcome the limitation of linear hierarchic structures and their mathematical consequences. This part on the ANP summarizes and illustrates the basic concepts of the ANP and shows how informed intuitive judgments can lead to real life answers that are matched by actual measurements in the real world (for example, relative dollar values) as illustrated in market share examples that rely on judgments and not on numerical data.
文摘This is the first part of an introduction to multicriteria decision making using the Analytic Hierarchy Process (AHP) and its generalization, the Analytic Network Process (ANP). The discussion involves individual and group decisions both with the independence of the criteria from the alternatives as in the AHP and also with dependence and feedback in the entire decision structure as in the ANP. This part explains the Analytic Hierarchy Process, with examples, and presents in some detail the mathematical foundations. An exposition of the Analytic Network Process and its applications will appear in later issues of this journal.
文摘The general theory of the ANP enables one to deal with the benefits,opportunities,costs,andrisks(the BOCR merits)of a decision,by introducing the notion of negative priorites for C and Ralong with the rating(not comparison)of the top priority alternative synthesized for each of the fourmerits in terms of strategic criteria to enable one to combine the four B,O,C,and R values of eachalternative into a single outcome.Strategic criteria are very basic criteria individuals and groups useto assess whether they should make any of the many decisions they face in their daily operations.They do not depend on any particular decision for their priorities but are assessed in terms of the goalsand values of the individual or organization.Synthesis is made with two formulas,one multiplicativeand one additive subtractive that can give rise to negative overall priorities.This paper summarizesand illustrates basic complex decisions involving several control criteria under each of the BOCRmerits.