In this work,the computational complexity of a spin-glass three-dimensional(3D)Ising model(for the lattice sizeN=lmn,wherel,m,n are thenumbersof lattice points along three crystallographic directions)is studied.We pro...In this work,the computational complexity of a spin-glass three-dimensional(3D)Ising model(for the lattice sizeN=lmn,wherel,m,n are thenumbersof lattice points along three crystallographic directions)is studied.We prove that an absolute minimum core(AMC)model consisting of a spin-glass 2D Ising model interacting with its nearest neighboring plane,has its computational complexity O(2mn).Any algorithms to make the model smaller(or simpler)than the AMC model will cut the basic element of the spin-glass 3D Ising model and lost many important information of the original model.Therefore,the computational complexity of the spin-glass 3D Ising model cannot be reduced to be less than O(2mn)by any algorithms,which is in subexponential time,superpolynomial.展开更多
The prediction of intrinsically disordered proteins is a hot research area in bio-information.Due to the high cost of experimental methods to evaluate disordered regions of protein sequences,it is becoming increasingl...The prediction of intrinsically disordered proteins is a hot research area in bio-information.Due to the high cost of experimental methods to evaluate disordered regions of protein sequences,it is becoming increasingly important to predict those regions through computational methods.In this paper,we developed a novel scheme by employing sequence complexity to calculate six features for each residue of a protein sequence,which includes the Shannon entropy,the topological entropy,the sample entropy and three amino acid preferences including Remark 465,Deleage/Roux,and Bfactor(2STD).Particularly,we introduced the sample entropy for calculating time series complexity by mapping the amino acid sequence to a time series of 0-9.To our knowledge,the sample entropy has not been previously used for predicting IDPs and hence is being used for the first time in our study.In addition,the scheme used a properly sized sliding window in every protein sequence which greatly improved the prediction performance.Finally,we used seven machine learning algorithms and tested with 10-fold cross-validation to get the results on the dataset R80 collected by Yang et al.and of the dataset DIS1556 from the Database of Protein Disorder(DisProt)(https://www.disprot.org)containing experimentally determined intrinsically disordered proteins(IDPs).The results showed that k-Nearest Neighbor was more appropriate and an overall prediction accuracy of 92%.Furthermore,our method just used six features and hence required lower computational complexity.展开更多
In this advanced exploration, we focus on multiple parameters estimation in bistatic Multiple-Input Multiple-Output(MIMO) radar systems, a crucial technique for target localization and imaging. Our research innovative...In this advanced exploration, we focus on multiple parameters estimation in bistatic Multiple-Input Multiple-Output(MIMO) radar systems, a crucial technique for target localization and imaging. Our research innovatively addresses the joint estimation of the Direction of Departure(DOD), Direction of Arrival(DOA), and Doppler frequency for incoherent targets. We propose a novel approach that significantly reduces computational complexity by utilizing the TemporalSpatial Nested Sampling Model(TSNSM). Our methodology begins with a multi-linear mapping mechanism to efficiently eliminate unnecessary virtual Degrees of Freedom(DOFs) and reorganize the remaining ones. We then employ the Toeplitz matrix triple iteration reconstruction method, surpassing the traditional Temporal-Spatial Smoothing Window(TSSW) approach, to mitigate the single snapshot effect and reduce computational demands. We further refine the highdimensional ESPRIT algorithm for joint estimation of DOD, DOA, and Doppler frequency, eliminating the need for additional parameter pairing. Moreover, we meticulously derive the Cramér-Rao Bound(CRB) for the TSNSM. This signal model allows for a second expansion of DOFs in time and space domains, achieving high precision in target angle and Doppler frequency estimation with low computational complexity. Our adaptable algorithm is validated through simulations and is suitable for sparse array MIMO radars with various structures, ensuring higher precision in parameter estimation with less complexity burden.展开更多
Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pP...Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.展开更多
Based on the iterative bit-filling procedure, a computationally efficient bit and power allocation algorithm is presented. The algorithm improves the conventional bit-filling algorithms by maintaining only a subset of...Based on the iterative bit-filling procedure, a computationally efficient bit and power allocation algorithm is presented. The algorithm improves the conventional bit-filling algorithms by maintaining only a subset of subcarriers for computation in each iteration, which reduces the complexity without any performance degradation. Moreover, a modified algorithm with even lower complexity is developed, and equal power allocation is introduced as an initial allocation to accelerate its convergence. Simulation results show that the modified algorithm achieves a considerable complexity reduction while causing only a minor drop in performance.展开更多
The spot flexibility markets are before the real-time energy exchange,allowing demand-side management to reduce energy consumption during peak periods.In these markets,demand aggregators must quickly choose the custom...The spot flexibility markets are before the real-time energy exchange,allowing demand-side management to reduce energy consumption during peak periods.In these markets,demand aggregators must quickly choose the customers’reduction bids that fulfill grid requirements.This clearing procedure is challenging due to the computational complexity of selecting the optimal bids.Therefore,developing a clearing mechanism that avoids searching the entire flexibility bid space while respecting grid constraints is essential for the smooth operation of the spot flexibility market.This paper presents a clearing mechanism with reduced computational complexity of the winner determination problem in spot flexibility market for demand aggregators carrying out reductions in energy consumption.The proposed approach transforms customers’flexibility bids into a reward-based function.Afterward,the gradient-based optimization solves the bid selection problem.This approach helps demand aggregators achieve satisfactory energy reductions within an appropriate delay for spot flexibility markets.A comparative study presents the effectiveness of the proposed approach against commonly used approaches:hybrid particle swarm optimization genetic algorithm and combinatorial search.展开更多
Navigation without Global Navigation Satellite Systems(GNSS)poses a significant challenge in aerospace engineering,particularly in the environments where satellite signals are obstructed or unavailable.This paper offe...Navigation without Global Navigation Satellite Systems(GNSS)poses a significant challenge in aerospace engineering,particularly in the environments where satellite signals are obstructed or unavailable.This paper offers an in-depth review of various methods,sensors,and algorithms for Unmanned Aerial Vehicle(UAV)localization in outdoor environments where GNSS signals are unavailable or denied.A key contribution of this study is the establishment of a critical classification system that divides GNSS-denied navigation techniques into two primary categories:absolute and relative localization.This classification enhances the understanding of the strengths and weaknesses of different strategies in various operational contexts.Vision-based localization is identified as the most effective approach in GNSS-denied environments.Nonetheless,it’s clear that no single-sensor-based localization algorithm can fulfill all the needs of a comprehensive navigation system in outdoor environments.Therefore,it’s vital to implement a hybrid strategy that merges various algorithms and sensors for effective outcomes.This detailed analysis emphasizes the challenges and possible solutions for achieving reliable and effective outdoor UAV localization in environments where GNSS is unreliable or unavailable.This multi-faceted analysis,highlights the complexities and potential pathways for achieving efficient and dependable outdoor UAV localization in GNSS-denied environments.展开更多
Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems,such as thermal power plants being studied in this work.Industrial processes are inherently d...Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems,such as thermal power plants being studied in this work.Industrial processes are inherently dynamic and need to be monitored using dynamic algorithms.Mainstream dynamic algorithms rely on concatenating current measurement with past data.This work proposes a new,alternative dynamic process monitoring algorithm,using dot product feature analysis(DPFA).DPFA computes the dot product of consecutive samples,thus naturally capturing the process dynamics through temporal correlation.At the same time,DPFA's online computational complexity is lower than not just existing dynamic algorithms,but also classical static algorithms(e.g.,principal component analysis and slow feature analysis).The detectability of the new algorithm is analyzed for three types of faults typically seen in process systems:sensor bias,process fault and gain change fault.Through experiments with a numerical example and real data from a thermal power plant,the DPFA algorithm is shown to be superior to the state-of-the-art methods,in terms of better monitoring performance(fault detection rate and false alarm rate)and lower computational complexity.展开更多
Safety maintenance of power equipment is of great importance in power grids,in which image-processing-based defect recognition is supposed to classify abnormal conditions during daily inspection.However,owing to the b...Safety maintenance of power equipment is of great importance in power grids,in which image-processing-based defect recognition is supposed to classify abnormal conditions during daily inspection.However,owing to the blurred features of defect images,the current defect recognition algorithm has poor fine-grained recognition ability.Visual attention can achieve fine-grained recognition with its abil-ity to model long-range dependencies while introducing extra computational complexity,especially for multi-head attention in vision transformer structures.Under these circumstances,this paper proposes a self-reduction multi-head attention module that can reduce computational complexity and be easily combined with a Convolutional Neural Network(CNN).In this manner,local and global fea-tures can be calculated simultaneously in our proposed structure,aiming to improve the defect recognition performance.Specifically,the proposed self-reduction multi-head attention can reduce redundant parameters,thereby solving the problem of limited computational resources.Experimental results were obtained based on the defect dataset collected from the substation.The results demonstrated the efficiency and superiority of the proposed method over other advanced algorithms.展开更多
Computational time complexity analyzes of evolutionary algorithms （EAs） have been performed since the mid-nineties. The first results were related to very simple algorithms, such as the （1＋1）-EA, on toy problems....Computational time complexity analyzes of evolutionary algorithms （EAs） have been performed since the mid-nineties. The first results were related to very simple algorithms, such as the （1＋1）-EA, on toy problems. These efforts produced a deeper understanding of how EAs perform on different kinds of fitness landscapes and general mathematical tools that may be extended to the analysis of more complicated EAs on more realistic problems. In fact, in recent years, it has been possible to analyze the （1＋1）-EA on combinatorial optimization problems with practical applications and more realistic population-based EAs on structured toy problems. This paper presents a survey of the results obtained in the last decade along these two research lines. The most common mathematical techniques are introduced, the basic ideas behind them are discussed and their elective applications are highlighted. Solved problems that were still open are enumerated as are those still awaiting for a solution. New questions and problems arisen in the meantime are also considered.展开更多
This paper proposes low-cost yet high-accuracy direction of arrival(DOA)estimation for the automotive frequency-modulated continuous-wave(FMcW)radar.The existing subspace-based DOA estimation algorithms suffer fromeit...This paper proposes low-cost yet high-accuracy direction of arrival(DOA)estimation for the automotive frequency-modulated continuous-wave(FMcW)radar.The existing subspace-based DOA estimation algorithms suffer fromeither high computational costs or low accuracy.We aim to solve such contradictory relation between complexity and accuracy by using randomizedmatrix approximation.Specifically,we apply an easily-interpretablerandomized low-rank approximation to the covariance matrix(CM)and R∈C^(M×M)throughthresketch maties in the fom of R≈OBQ^(H).Here the approximately compute its subspaces.That is,we first approximate matrix Q∈C^(M×z)contains the orthonormal basis for the range of the sketchmatrik C∈C^(M×z)cwe whichis etrated fom R using randomized unifom counsampling and B∈C^(z×z)is a weight-matrix reducing the approximation error.Relying on such approximation,we are able to accelerate the subspacecomputation by the orders of the magnitude without compromising estimation accuracy.Furthermore,we drive a theoretical error bound for the suggested scheme to ensure the accuracy of the approximation.As validated by the simulation results,the DOA estimation accuracy of the proposed algorithm,eficient multiple signal classification(E-MUSIC)s high,closely tracks standardMUSIC,and outperforms the well-known algorithms with tremendouslyreduced time complexity.Thus,the devised method can realize high-resolutionreal-time target detection in the emerging multiple input and multiple output(MIMO)automotive radar systems.展开更多
For future wireless communication systems,Power Domain Non-Orthogonal Multiple Access(PD-NOMA)using an advanced receiver has been considered as a promising radio access technology candidate.Power allocation plays an i...For future wireless communication systems,Power Domain Non-Orthogonal Multiple Access(PD-NOMA)using an advanced receiver has been considered as a promising radio access technology candidate.Power allocation plays an important role in the PD-NOMA system because it considerably affects the total throughput and Geometric Mean User Throughput(GMUT)performance.However,most existing studies have not completely accounted for the computational complexity of the power allocation process when the User Terminals(UTs)move in a slow fading channel environment.To resolve such problems,a power allocation method is proposed to considerably reduce the search space of a Full Search Power(FSP)allocation algorithm.The initial power reallocation coefficients will be set to start with former optimal values by the proposed Lemma before searching for optimal power reallocation coefficients based on total throughput performance.Step size and correction granularity will be adjusted within a much narrower power search range while invalid power combinations may be reasonably discarded during the search process.The simulation results show that the proposed power reallocation scheme can greatly reduce computational complexity while the total throughput and GMUT performance loss are not greater than 1.5%compared with the FSP algorithm.展开更多
Nested linear array enables to enhance localization resolution and achieve under-determined direction of arrival(DOA)estimation.In this paper,the traditional two-level nested linear array is improved to achieve more d...Nested linear array enables to enhance localization resolution and achieve under-determined direction of arrival(DOA)estimation.In this paper,the traditional two-level nested linear array is improved to achieve more degrees of freedom(DOFs)and better angle estimation performance.Furthermore,a computationally efficient DOA estimation algorithm is proposed.The discrete Fourier transform(DFT)method is utilized to obtain coarse DOA estimates,and subsequently,fine DOA estimates are achieved by spatial smoothing multiple signals classification(SS-MUSIC)algorithm.Compared to SS-MUSIC algorithm,the proposed algorithm has the same estimation accuracy with lower computational complexity because the coarse DOA estimates enable to shrink the range of angle spectral search.In addition,the estimation of the number of signals is not required in advance by DFT method.Extensive simulation results testify the effectiveness of the proposed algorithm.展开更多
The variable block-size motion estimation(ME) and disparity estimation(DE) are adopted in multi-view video coding(MVC) to achieve high coding efficiency. However, much higher computational complexity is also introduce...The variable block-size motion estimation(ME) and disparity estimation(DE) are adopted in multi-view video coding(MVC) to achieve high coding efficiency. However, much higher computational complexity is also introduced in coding system, which hinders practical application of MVC. An efficient fast mode decision method using mode complexity is proposed to reduce the computational complexity. In the proposed method, mode complexity is firstly computed by using the spatial, temporal and inter-view correlation between the current macroblock(MB) and its neighboring MBs. Based on the observation that direct mode is highly possible to be the optimal mode, mode complexity is always checked in advance whether it is below a predefined threshold for providing an efficient early termination opportunity. If this early termination condition is not met, three mode types for the MBs are classified according to the value of mode complexity, i.e., simple mode, medium mode and complex mode, to speed up the encoding process by reducing the number of the variable block modes required to be checked. Furthermore, for simple and medium mode region, the rate distortion(RD) cost of mode 16×16 in the temporal prediction direction is compared with that of the disparity prediction direction, to determine in advance whether the optimal prediction direction is in the temporal prediction direction or not, for skipping unnecessary disparity estimation. Experimental results show that the proposed method is able to significantly reduce the computational load by 78.79% and the total bit rate by 0.07% on average, while only incurring a negligible loss of PSNR(about 0.04 d B on average), compared with the full mode decision(FMD) in the reference software of MVC.展开更多
The title complex is widely used as an efficient key component of Ziegler-Natta catalyst for stereospecific polymerization of dienes to produce synthetic rubbers. However, the quantitative structure-activity relations...The title complex is widely used as an efficient key component of Ziegler-Natta catalyst for stereospecific polymerization of dienes to produce synthetic rubbers. However, the quantitative structure-activity relationship（QSAR） of this kind of complexes is still not clear mainly due to the difficulties to obtain their geometric molecular structures through laboratory experiments. An alternative solution is the quantum chemistry calculation in which the comformational population shall be determined. In this study, ten conformers of the title complex were obtained with the function of molecular dynamics conformational search in Gabedit 2.4.8, and their geometry optimization and thermodynamics calculation were made with a Sparkle/PM7 approach in MOPAC 2012. Their Gibbs free energies at 1 atm. and 298.15 K were calculated. Population of the conformers was further calculated out according to the theory of Boltzmann distribution, indicating that one of the ten conformers has a dominant population of 77.13%.展开更多
In this paper, a real-time computation method for the control problems in differential-algebraic systems is presented. The errors of the method are estimated, and the relation between the sampling stepsize and the con...In this paper, a real-time computation method for the control problems in differential-algebraic systems is presented. The errors of the method are estimated, and the relation between the sampling stepsize and the controlled errors is analyzed. The stability analysis is done for a model problem, and the stability region is ploted which gives the range of the sampling stepsizes with which the stability of control process is guaranteed.展开更多
First,an explicit representation A(2)T,S=(GA+E)^-1G of the outer invers A(2)T,S for a matrix A∈Cm×n with the prescribed range T and null space S is derived,which is simpler than A(2)T,S=(GA+E)^-1G-V(UV)-2UG prop...First,an explicit representation A(2)T,S=(GA+E)^-1G of the outer invers A(2)T,S for a matrix A∈Cm×n with the prescribed range T and null space S is derived,which is simpler than A(2)T,S=(GA+E)^-1G-V(UV)-2UG proposed by Ji in 2005.Next,a new algorithm for computing the outer inverse A(2)T,S based on the improved representation A(2)T,S=(GA+E)^-1G through elementary operations on an appropriate partitioned matrix GAInIn0 is proposed and investigated.Then,the computational complexity of the introduced algorithm is also analyzed in detail.Finally,two numerical examples are shown to illustrate that this method is correct.展开更多
In this article the inherent computational power of the quantum entangled cluster states examined by measurement-based quantum computations is studied. By defining a common framework of rules for measurement of quantu...In this article the inherent computational power of the quantum entangled cluster states examined by measurement-based quantum computations is studied. By defining a common framework of rules for measurement of quantum entangled cluster states based on classical computations, the precise and detailed meaning of the computing power of the correlations in the quantum cluster states is made. This study exposes a connection, arousing interest, between the infringement of the realistic models that are local and the computing power of the quantum entangled cluster states.展开更多
The use of the Internet of Things(IoT)is expanding at an unprecedented scale in many critical applications due to the ability to interconnect and utilize a plethora of wide range of devices.In critical infrastructure ...The use of the Internet of Things(IoT)is expanding at an unprecedented scale in many critical applications due to the ability to interconnect and utilize a plethora of wide range of devices.In critical infrastructure domains like oil and gas supply,intelligent transportation,power grids,and autonomous agriculture,it is essential to guarantee the confidentiality,integrity,and authenticity of data collected and exchanged.However,the limited resources coupled with the heterogeneity of IoT devices make it inefficient or sometimes infeasible to achieve secure data transmission using traditional cryptographic techniques.Consequently,designing a lightweight secure data transmission scheme is becoming essential.In this article,we propose lightweight secure data transmission(LSDT)scheme for IoT environments.LSDT consists of three phases and utilizes an effective combination of symmetric keys and the Elliptic Curve Menezes-Qu-Vanstone asymmetric key agreement protocol.We design the simulation environment and experiments to evaluate the performance of the LSDT scheme in terms of communication and computation costs.Security and performance analysis indicates that the LSDT scheme is secure,suitable for IoT applications,and performs better in comparison to other related security schemes.展开更多
A new selected mapping(SLM)scheme based on constellation rotation is proposed to reduce the peak-to-average power ratio(PAPR)of orthogonal frequency division multiplexing(OFDM)signals.Its core idea is to generate abun...A new selected mapping(SLM)scheme based on constellation rotation is proposed to reduce the peak-to-average power ratio(PAPR)of orthogonal frequency division multiplexing(OFDM)signals.Its core idea is to generate abundant candidate signals by rotating different sub-signals of the original frequency signal with different angles.This new signal generation method can simplify the calculation process of candidate time signals into the linear addition of some intermediate signals,which are generated by the inverse fast Fourier transform(IFFT)operation of the original frequency signal.This feature can effectively reduce the computational complexity of candidate signal generation process.And compared to the traditional SLM scheme,the number of complex multiplication and complex addition of new scheme can separately be decreased by about 99.99% and 91.7% with some specific parameters.Moreover,with the help of the constellation detection mechanism at the receiver,there is no need to carry any side information at the transmitter.The simulation results show that,with the same channel transmission performance,the PAPR reduction performance of new scheme can approach or even exceed the upper bound of the traditional SLM scheme,which uses all the vectors in Hadamard matrix as the phase sequences.展开更多
基金This work has been supported by the National Natural Science Foundation of China under grant numbers 51590883 and 51331006by the State Key Project of Research and Development of China(No.2017YFA0206302).
文摘In this work,the computational complexity of a spin-glass three-dimensional(3D)Ising model(for the lattice sizeN=lmn,wherel,m,n are thenumbersof lattice points along three crystallographic directions)is studied.We prove that an absolute minimum core(AMC)model consisting of a spin-glass 2D Ising model interacting with its nearest neighboring plane,has its computational complexity O(2mn).Any algorithms to make the model smaller(or simpler)than the AMC model will cut the basic element of the spin-glass 3D Ising model and lost many important information of the original model.Therefore,the computational complexity of the spin-glass 3D Ising model cannot be reduced to be less than O(2mn)by any algorithms,which is in subexponential time,superpolynomial.
文摘The prediction of intrinsically disordered proteins is a hot research area in bio-information.Due to the high cost of experimental methods to evaluate disordered regions of protein sequences,it is becoming increasingly important to predict those regions through computational methods.In this paper,we developed a novel scheme by employing sequence complexity to calculate six features for each residue of a protein sequence,which includes the Shannon entropy,the topological entropy,the sample entropy and three amino acid preferences including Remark 465,Deleage/Roux,and Bfactor(2STD).Particularly,we introduced the sample entropy for calculating time series complexity by mapping the amino acid sequence to a time series of 0-9.To our knowledge,the sample entropy has not been previously used for predicting IDPs and hence is being used for the first time in our study.In addition,the scheme used a properly sized sliding window in every protein sequence which greatly improved the prediction performance.Finally,we used seven machine learning algorithms and tested with 10-fold cross-validation to get the results on the dataset R80 collected by Yang et al.and of the dataset DIS1556 from the Database of Protein Disorder(DisProt)(https://www.disprot.org)containing experimentally determined intrinsically disordered proteins(IDPs).The results showed that k-Nearest Neighbor was more appropriate and an overall prediction accuracy of 92%.Furthermore,our method just used six features and hence required lower computational complexity.
基金supported in part by the National Natural Science Foundation of China(No.62071476)in part by China Postdoctoral Science Foundation(No.2022M723879)in part by the Science and Technology Innovation Program of Hunan Province,China(No.2021RC3080)。
文摘In this advanced exploration, we focus on multiple parameters estimation in bistatic Multiple-Input Multiple-Output(MIMO) radar systems, a crucial technique for target localization and imaging. Our research innovatively addresses the joint estimation of the Direction of Departure(DOD), Direction of Arrival(DOA), and Doppler frequency for incoherent targets. We propose a novel approach that significantly reduces computational complexity by utilizing the TemporalSpatial Nested Sampling Model(TSNSM). Our methodology begins with a multi-linear mapping mechanism to efficiently eliminate unnecessary virtual Degrees of Freedom(DOFs) and reorganize the remaining ones. We then employ the Toeplitz matrix triple iteration reconstruction method, surpassing the traditional Temporal-Spatial Smoothing Window(TSSW) approach, to mitigate the single snapshot effect and reduce computational demands. We further refine the highdimensional ESPRIT algorithm for joint estimation of DOD, DOA, and Doppler frequency, eliminating the need for additional parameter pairing. Moreover, we meticulously derive the Cramér-Rao Bound(CRB) for the TSNSM. This signal model allows for a second expansion of DOFs in time and space domains, achieving high precision in target angle and Doppler frequency estimation with low computational complexity. Our adaptable algorithm is validated through simulations and is suitable for sparse array MIMO radars with various structures, ensuring higher precision in parameter estimation with less complexity burden.
基金supported by the Deanship of Graduate Studies and Scientific Research at Qassim University(QU-APC-2024-9/1).
文摘Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.
基金The National High Technology Research and Devel-opment Program of China (863Program) (No2006AA01Z263)the National Natural Science Foundation of China (No60496311)
文摘Based on the iterative bit-filling procedure, a computationally efficient bit and power allocation algorithm is presented. The algorithm improves the conventional bit-filling algorithms by maintaining only a subset of subcarriers for computation in each iteration, which reduces the complexity without any performance degradation. Moreover, a modified algorithm with even lower complexity is developed, and equal power allocation is introduced as an initial allocation to accelerate its convergence. Simulation results show that the modified algorithm achieves a considerable complexity reduction while causing only a minor drop in performance.
基金the Laboratoire des Technologies de l’énergie d’Hydro-Québec,the Natural Science and Engineering Research Council of Canada,and the Foundation of Universitédu QuébecàTrois-Rivières.
文摘The spot flexibility markets are before the real-time energy exchange,allowing demand-side management to reduce energy consumption during peak periods.In these markets,demand aggregators must quickly choose the customers’reduction bids that fulfill grid requirements.This clearing procedure is challenging due to the computational complexity of selecting the optimal bids.Therefore,developing a clearing mechanism that avoids searching the entire flexibility bid space while respecting grid constraints is essential for the smooth operation of the spot flexibility market.This paper presents a clearing mechanism with reduced computational complexity of the winner determination problem in spot flexibility market for demand aggregators carrying out reductions in energy consumption.The proposed approach transforms customers’flexibility bids into a reward-based function.Afterward,the gradient-based optimization solves the bid selection problem.This approach helps demand aggregators achieve satisfactory energy reductions within an appropriate delay for spot flexibility markets.A comparative study presents the effectiveness of the proposed approach against commonly used approaches:hybrid particle swarm optimization genetic algorithm and combinatorial search.
基金funded by PSDSARC seed project number(PSDSARC Project ID:PID-000085_01_02)the APC was funded by PSU.
文摘Navigation without Global Navigation Satellite Systems(GNSS)poses a significant challenge in aerospace engineering,particularly in the environments where satellite signals are obstructed or unavailable.This paper offers an in-depth review of various methods,sensors,and algorithms for Unmanned Aerial Vehicle(UAV)localization in outdoor environments where GNSS signals are unavailable or denied.A key contribution of this study is the establishment of a critical classification system that divides GNSS-denied navigation techniques into two primary categories:absolute and relative localization.This classification enhances the understanding of the strengths and weaknesses of different strategies in various operational contexts.Vision-based localization is identified as the most effective approach in GNSS-denied environments.Nonetheless,it’s clear that no single-sensor-based localization algorithm can fulfill all the needs of a comprehensive navigation system in outdoor environments.Therefore,it’s vital to implement a hybrid strategy that merges various algorithms and sensors for effective outcomes.This detailed analysis emphasizes the challenges and possible solutions for achieving reliable and effective outdoor UAV localization in environments where GNSS is unreliable or unavailable.This multi-faceted analysis,highlights the complexities and potential pathways for achieving efficient and dependable outdoor UAV localization in GNSS-denied environments.
基金supported in part by the National Science Fund for Distinguished Young Scholars of China(62225303)the National Natural Science Fundation of China(62303039,62433004)+2 种基金the China Postdoctoral Science Foundation(BX20230034,2023M730190)the Fundamental Research Funds for the Central Universities(buctrc202201,QNTD2023-01)the High Performance Computing Platform,College of Information Science and Technology,Beijing University of Chemical Technology
文摘Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems,such as thermal power plants being studied in this work.Industrial processes are inherently dynamic and need to be monitored using dynamic algorithms.Mainstream dynamic algorithms rely on concatenating current measurement with past data.This work proposes a new,alternative dynamic process monitoring algorithm,using dot product feature analysis(DPFA).DPFA computes the dot product of consecutive samples,thus naturally capturing the process dynamics through temporal correlation.At the same time,DPFA's online computational complexity is lower than not just existing dynamic algorithms,but also classical static algorithms(e.g.,principal component analysis and slow feature analysis).The detectability of the new algorithm is analyzed for three types of faults typically seen in process systems:sensor bias,process fault and gain change fault.Through experiments with a numerical example and real data from a thermal power plant,the DPFA algorithm is shown to be superior to the state-of-the-art methods,in terms of better monitoring performance(fault detection rate and false alarm rate)and lower computational complexity.
基金supported in part by Major Program of the National Natural Science Foundation of China under Grant 62127803.
文摘Safety maintenance of power equipment is of great importance in power grids,in which image-processing-based defect recognition is supposed to classify abnormal conditions during daily inspection.However,owing to the blurred features of defect images,the current defect recognition algorithm has poor fine-grained recognition ability.Visual attention can achieve fine-grained recognition with its abil-ity to model long-range dependencies while introducing extra computational complexity,especially for multi-head attention in vision transformer structures.Under these circumstances,this paper proposes a self-reduction multi-head attention module that can reduce computational complexity and be easily combined with a Convolutional Neural Network(CNN).In this manner,local and global fea-tures can be calculated simultaneously in our proposed structure,aiming to improve the defect recognition performance.Specifically,the proposed self-reduction multi-head attention can reduce redundant parameters,thereby solving the problem of limited computational resources.Experimental results were obtained based on the defect dataset collected from the substation.The results demonstrated the efficiency and superiority of the proposed method over other advanced algorithms.
基金This work was supported by an EPSRC grant (No.EP/C520696/1).
文摘Computational time complexity analyzes of evolutionary algorithms （EAs） have been performed since the mid-nineties. The first results were related to very simple algorithms, such as the （1＋1）-EA, on toy problems. These efforts produced a deeper understanding of how EAs perform on different kinds of fitness landscapes and general mathematical tools that may be extended to the analysis of more complicated EAs on more realistic problems. In fact, in recent years, it has been possible to analyze the （1＋1）-EA on combinatorial optimization problems with practical applications and more realistic population-based EAs on structured toy problems. This paper presents a survey of the results obtained in the last decade along these two research lines. The most common mathematical techniques are introduced, the basic ideas behind them are discussed and their elective applications are highlighted. Solved problems that were still open are enumerated as are those still awaiting for a solution. New questions and problems arisen in the meantime are also considered.
文摘This paper proposes low-cost yet high-accuracy direction of arrival(DOA)estimation for the automotive frequency-modulated continuous-wave(FMcW)radar.The existing subspace-based DOA estimation algorithms suffer fromeither high computational costs or low accuracy.We aim to solve such contradictory relation between complexity and accuracy by using randomizedmatrix approximation.Specifically,we apply an easily-interpretablerandomized low-rank approximation to the covariance matrix(CM)and R∈C^(M×M)throughthresketch maties in the fom of R≈OBQ^(H).Here the approximately compute its subspaces.That is,we first approximate matrix Q∈C^(M×z)contains the orthonormal basis for the range of the sketchmatrik C∈C^(M×z)cwe whichis etrated fom R using randomized unifom counsampling and B∈C^(z×z)is a weight-matrix reducing the approximation error.Relying on such approximation,we are able to accelerate the subspacecomputation by the orders of the magnitude without compromising estimation accuracy.Furthermore,we drive a theoretical error bound for the suggested scheme to ensure the accuracy of the approximation.As validated by the simulation results,the DOA estimation accuracy of the proposed algorithm,eficient multiple signal classification(E-MUSIC)s high,closely tracks standardMUSIC,and outperforms the well-known algorithms with tremendouslyreduced time complexity.Thus,the devised method can realize high-resolutionreal-time target detection in the emerging multiple input and multiple output(MIMO)automotive radar systems.
基金supported in part by the Science and Technology Research Program of the National Science Foundation of China(61671096)Chongqing Research Program of Basic Science and Frontier Technology(cstc2017jcyjBX0005)+1 种基金Chongqing Municipal Education Commission(KJQN201800642)Doctoral Student Training Program(BYJS2016009).
文摘For future wireless communication systems,Power Domain Non-Orthogonal Multiple Access(PD-NOMA)using an advanced receiver has been considered as a promising radio access technology candidate.Power allocation plays an important role in the PD-NOMA system because it considerably affects the total throughput and Geometric Mean User Throughput(GMUT)performance.However,most existing studies have not completely accounted for the computational complexity of the power allocation process when the User Terminals(UTs)move in a slow fading channel environment.To resolve such problems,a power allocation method is proposed to considerably reduce the search space of a Full Search Power(FSP)allocation algorithm.The initial power reallocation coefficients will be set to start with former optimal values by the proposed Lemma before searching for optimal power reallocation coefficients based on total throughput performance.Step size and correction granularity will be adjusted within a much narrower power search range while invalid power combinations may be reasonably discarded during the search process.The simulation results show that the proposed power reallocation scheme can greatly reduce computational complexity while the total throughput and GMUT performance loss are not greater than 1.5%compared with the FSP algorithm.
基金supported by the Postgraduate Research & Practice Innovation Program of Jiangsu Province (No.SJCX18_0103)Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space (Nanjing University of Aeronautics and Astronautics), Ministry of Industry and Information Technology (No.KF20181915)
文摘Nested linear array enables to enhance localization resolution and achieve under-determined direction of arrival(DOA)estimation.In this paper,the traditional two-level nested linear array is improved to achieve more degrees of freedom(DOFs)and better angle estimation performance.Furthermore,a computationally efficient DOA estimation algorithm is proposed.The discrete Fourier transform(DFT)method is utilized to obtain coarse DOA estimates,and subsequently,fine DOA estimates are achieved by spatial smoothing multiple signals classification(SS-MUSIC)algorithm.Compared to SS-MUSIC algorithm,the proposed algorithm has the same estimation accuracy with lower computational complexity because the coarse DOA estimates enable to shrink the range of angle spectral search.In addition,the estimation of the number of signals is not required in advance by DFT method.Extensive simulation results testify the effectiveness of the proposed algorithm.
基金Project(08Y29-7)supported by the Transportation Science and Research Program of Jiangsu Province,ChinaProject(201103051)supported by the Major Infrastructure Program of the Health Monitoring System Hardware Platform Based on Sensor Network Node,China+1 种基金Project(61100111)supported by the National Natural Science Foundation of ChinaProject(BE2011169)supported by the Scientific and Technical Supporting Program of Jiangsu Province,China
文摘The variable block-size motion estimation(ME) and disparity estimation(DE) are adopted in multi-view video coding(MVC) to achieve high coding efficiency. However, much higher computational complexity is also introduced in coding system, which hinders practical application of MVC. An efficient fast mode decision method using mode complexity is proposed to reduce the computational complexity. In the proposed method, mode complexity is firstly computed by using the spatial, temporal and inter-view correlation between the current macroblock(MB) and its neighboring MBs. Based on the observation that direct mode is highly possible to be the optimal mode, mode complexity is always checked in advance whether it is below a predefined threshold for providing an efficient early termination opportunity. If this early termination condition is not met, three mode types for the MBs are classified according to the value of mode complexity, i.e., simple mode, medium mode and complex mode, to speed up the encoding process by reducing the number of the variable block modes required to be checked. Furthermore, for simple and medium mode region, the rate distortion(RD) cost of mode 16×16 in the temporal prediction direction is compared with that of the disparity prediction direction, to determine in advance whether the optimal prediction direction is in the temporal prediction direction or not, for skipping unnecessary disparity estimation. Experimental results show that the proposed method is able to significantly reduce the computational load by 78.79% and the total bit rate by 0.07% on average, while only incurring a negligible loss of PSNR(about 0.04 d B on average), compared with the full mode decision(FMD) in the reference software of MVC.
基金supported by the National Natural Science Foundation of China(No.21476119)
文摘The title complex is widely used as an efficient key component of Ziegler-Natta catalyst for stereospecific polymerization of dienes to produce synthetic rubbers. However, the quantitative structure-activity relationship（QSAR） of this kind of complexes is still not clear mainly due to the difficulties to obtain their geometric molecular structures through laboratory experiments. An alternative solution is the quantum chemistry calculation in which the comformational population shall be determined. In this study, ten conformers of the title complex were obtained with the function of molecular dynamics conformational search in Gabedit 2.4.8, and their geometry optimization and thermodynamics calculation were made with a Sparkle/PM7 approach in MOPAC 2012. Their Gibbs free energies at 1 atm. and 298.15 K were calculated. Population of the conformers was further calculated out according to the theory of Boltzmann distribution, indicating that one of the ten conformers has a dominant population of 77.13%.
文摘In this paper, a real-time computation method for the control problems in differential-algebraic systems is presented. The errors of the method are estimated, and the relation between the sampling stepsize and the controlled errors is analyzed. The stability analysis is done for a model problem, and the stability region is ploted which gives the range of the sampling stepsizes with which the stability of control process is guaranteed.
基金The National Natural Science Foundation of China(No.11771076).
文摘First,an explicit representation A(2)T,S=(GA+E)^-1G of the outer invers A(2)T,S for a matrix A∈Cm×n with the prescribed range T and null space S is derived,which is simpler than A(2)T,S=(GA+E)^-1G-V(UV)-2UG proposed by Ji in 2005.Next,a new algorithm for computing the outer inverse A(2)T,S based on the improved representation A(2)T,S=(GA+E)^-1G through elementary operations on an appropriate partitioned matrix GAInIn0 is proposed and investigated.Then,the computational complexity of the introduced algorithm is also analyzed in detail.Finally,two numerical examples are shown to illustrate that this method is correct.
文摘In this article the inherent computational power of the quantum entangled cluster states examined by measurement-based quantum computations is studied. By defining a common framework of rules for measurement of quantum entangled cluster states based on classical computations, the precise and detailed meaning of the computing power of the correlations in the quantum cluster states is made. This study exposes a connection, arousing interest, between the infringement of the realistic models that are local and the computing power of the quantum entangled cluster states.
基金support of the Interdisciplinary Research Center for Intelligent Secure Systems(IRC-ISS)Internal Fund Grant#INSS2202.
文摘The use of the Internet of Things(IoT)is expanding at an unprecedented scale in many critical applications due to the ability to interconnect and utilize a plethora of wide range of devices.In critical infrastructure domains like oil and gas supply,intelligent transportation,power grids,and autonomous agriculture,it is essential to guarantee the confidentiality,integrity,and authenticity of data collected and exchanged.However,the limited resources coupled with the heterogeneity of IoT devices make it inefficient or sometimes infeasible to achieve secure data transmission using traditional cryptographic techniques.Consequently,designing a lightweight secure data transmission scheme is becoming essential.In this article,we propose lightweight secure data transmission(LSDT)scheme for IoT environments.LSDT consists of three phases and utilizes an effective combination of symmetric keys and the Elliptic Curve Menezes-Qu-Vanstone asymmetric key agreement protocol.We design the simulation environment and experiments to evaluate the performance of the LSDT scheme in terms of communication and computation costs.Security and performance analysis indicates that the LSDT scheme is secure,suitable for IoT applications,and performs better in comparison to other related security schemes.
文摘A new selected mapping(SLM)scheme based on constellation rotation is proposed to reduce the peak-to-average power ratio(PAPR)of orthogonal frequency division multiplexing(OFDM)signals.Its core idea is to generate abundant candidate signals by rotating different sub-signals of the original frequency signal with different angles.This new signal generation method can simplify the calculation process of candidate time signals into the linear addition of some intermediate signals,which are generated by the inverse fast Fourier transform(IFFT)operation of the original frequency signal.This feature can effectively reduce the computational complexity of candidate signal generation process.And compared to the traditional SLM scheme,the number of complex multiplication and complex addition of new scheme can separately be decreased by about 99.99% and 91.7% with some specific parameters.Moreover,with the help of the constellation detection mechanism at the receiver,there is no need to carry any side information at the transmitter.The simulation results show that,with the same channel transmission performance,the PAPR reduction performance of new scheme can approach or even exceed the upper bound of the traditional SLM scheme,which uses all the vectors in Hadamard matrix as the phase sequences.
