Advancing 3D magnesium(Mg)development beyond current limitations requires controlling Mg alloy degradation in pre-designed,low-dimension architectures.This study reveals a mechanistic switch in the corrosion behavior ...Advancing 3D magnesium(Mg)development beyond current limitations requires controlling Mg alloy degradation in pre-designed,low-dimension architectures.This study reveals a mechanistic switch in the corrosion behavior of Mg alloy(3.6%Al,0.8%Zn)diamond lattice structures,induced by plasma nanosynthesis(400 eV Ar^(+)ions,fluence 1×10^(17) ions/cm^(2)).Plasma treatment of the Mg alloy increases surface Mg from 1.5%to 14.5%,enhances carbonate formation,and generates a nanostructured surface with a Mg carbonate layer over an oxide/hydroxide layer.In vitro and in vivo analyses over 8 wk demonstrate how this treatment fundamentally alters the degradation process and stability of these 3D architectures.While untreated samples initially formed a protective film that subsequently diminished,DPNS-treated samples demonstrated an inverse corrosion behavior.X-ray photoelectron spectroscopy(XPS)and electrochemical impedance spectroscopy(EIS)confirmed the presence of a stable,protective layer composed of magnesium oxide,magnesium hydroxide,and magnesium carbonate on the DPNS-treated surfaces.After 14 days,the DPNS-treated sample exhibited a more positive corrosion potential(-0.69 V versus-1.36 V)and a marginally lower current density(0.73 mA/cm^(2)compared to 0.75 mA/c^(2))relative to the control.This protective layer,combined with modified surface topology,initiated a core-to-periphery degradation pattern that maintained structural integrity for up to 8 wk post-implantation.These findings support the conclusion that the DPNS-treated scaffold demonstrates sustained improved corrosion resistance over time compared to the untreated control.Micro-CT revealed plasma-treated samples retained larger struts(504.9±95.3μm at 8 wk)and formed larger H_(2) pockets extending 14.2 mm from the implant center,versus 4.9 mm in controls.This corrosion behavior switch enhances stability but risks pore clogging,offering insights for tailoring Mg alloy degradation and H_(2) evolution in 3D architectures for biomedical applications.展开更多
Recyclability and self-healing are two most critical factors in developing sustainable polymers to deal with environmental pollution and resource waste.In this work,a dynamic cross-linked polyimide insulation film wit...Recyclability and self-healing are two most critical factors in developing sustainable polymers to deal with environmental pollution and resource waste.In this work,a dynamic cross-linked polyimide insulation film with full closed-loop recyclability is successfully prepared,which also possesses good self-healing ability after being mechanical/electrical damaged depending on the Schiff base dynamic covalent bonds.The recycled and self-healed polyimide film still maintain its good tensile strength(r t)>60 MPa with Young’s modulus(E)>4 GPa,high thermal stability with glass transition temperature(T g)>220℃,and outstanding insulation property with breakdown strength(E 0)>358 kV mm^(-1),making it a very promising low energy consumption and high temperature resistant insulation material.The strategy of using Schiff base dynamic covalent bonds for reversible repairing the structure of high T g polyimides promotes the wider application of such sustainable and recyclable material in the field of electrical power and micro-electronics.展开更多
Artificial intelligence and computer vision need methods for 2D （two-dimensional） shape retrieval having discrete set of boundary points. A novel method of MHR （Hurwitz-Radon Matrices） is used in shape modeling. P...Artificial intelligence and computer vision need methods for 2D （two-dimensional） shape retrieval having discrete set of boundary points. A novel method of MHR （Hurwitz-Radon Matrices） is used in shape modeling. Proposed method is based on the family of MHR which possess columns composed of orthogonal vectors. 2D curve is retrieved via different functions as probability distribution functions： sine, cosine, tangent, logarithm, exponent, arcsin, arccos, arctan and power function. Created from the family of N-1 MHR and completed with the identical matrix, system of matrices is orthogonal only for dimensions N = 2, 4 or 8. Orthogonality of columns and rows is very significant for stability and high precision of calculations. MHR method is interpolating the function point by point without using any formula of function. Main features of MHR method are： accuracy of curve reconstruction depending on number of nodes and method of choosing nodes, interpolation of L points of the curve is connected with the computational cost of rank O（L）, MHR interpolation is not a linear interpolation.展开更多
This paper presents discrete wavelet transform （DWT） and its inverse （IDWT） with Haar wavelets as tools to compute the variable size interpolated versions of an image at optimum computational load. As a human obse...This paper presents discrete wavelet transform （DWT） and its inverse （IDWT） with Haar wavelets as tools to compute the variable size interpolated versions of an image at optimum computational load. As a human observer moves closer to or farther from a scene, the retinal image of the scene zooms in or out, respectively. This zooming in or out can be modeled using variable scale interpolation. The paper proposes a novel way of applying DWT and IDWT in a piecewise manner by non-uniform down- or up-sampling of the images to achieve partially sampled versions of the images. The partially sampled versions are then aggregated to achieve the final variable scale interpolated images. The non-uniform down- or up-sampling here is a function of the required scale of interpolation. Appropriate zero padding is used to make the images suitable for the required non-uniform sampling and the subsequent interpolation to the required scale. The concept of zeroeth level DWT is introduced here, which works as the basis for interpolating the images to achieve bigger size than the original one. The main emphasis here is on the computation of variable size images at less computational load, without compromise of quality of images. The interpolated images to different sizes and the reconstructed images are benchmarked using the statistical parameters and visual comparison. It has been found that the proposed approach performs better as compared to bilinear and bicubic interpolation techniques.展开更多
In past years,growing efforts have been made to the rapid interpretation of magnetic field data acquired by a sparse synthetic or real magnetic sensor array.An appealing requirement on such sparse array arranged withi...In past years,growing efforts have been made to the rapid interpretation of magnetic field data acquired by a sparse synthetic or real magnetic sensor array.An appealing requirement on such sparse array arranged within a specified survey region is that to make the number of sensor elements as small as possible,meanwhile without deteriorating imaging quality.For this end,we propose a novel methodology of arranging sensors in an optimal manner,exploring the concept of information capacity developed originally in the communication society.The proposed scheme reduces mathematically the design of a sparse sensor array into solving a combinatorial optimization problem,which can be resolved efficiently using widely adopted Simultaneous Perturbation and Statistical Algorithm(SPSA).Three sets of numerical examples of designing optimal sensor array are provided to demonstrate the performance of proposed methodology.展开更多
Image analysis and computer vision are interested in suitable methods to solve the nonlinear equations. Coordinate x??for f (x)?= 0?is crucial because each equation can be transformed into f (x)?= 0. A novel method of...Image analysis and computer vision are interested in suitable methods to solve the nonlinear equations. Coordinate x??for f (x)?= 0?is crucial because each equation can be transformed into f (x)?= 0. A novel method of Hurwitz-Radon Matrices (MHR) can be used in approximation of a root of function in the plane. The paper contains a way of data approximation via MHR method to solve any equation. Proposed method is based on the family of Hurwitz-Radon (HR) matrices. The matrices are skew-symmetric and possess columns composed of orthogonal vectors. The operator of Hurwitz-Radon (OHR), built from these matrices, is described. Two-dimensional data are represented by discrete set of curve??f points. It is shown how to create the orthogonal OHR operator and how to use it in a process of data interpolation. MHR method is interpolating the curve point by point without using any formula or function.展开更多
We report a method for the coacervation micro-encapsulation of several forms of CaCO3 microparticles with the fluoropolymer poly(heptadecafluorodecyl acrylate) (poly (HDFDA)) by pressure-induced phase separation of a ...We report a method for the coacervation micro-encapsulation of several forms of CaCO3 microparticles with the fluoropolymer poly(heptadecafluorodecyl acrylate) (poly (HDFDA)) by pressure-induced phase separation of a supercritical CO2 solution.? A suspension of CaCO3 in CO2 and dissolved poly(HDFDA) were mixed in supercritical CO2.? After the system pressure was slowly decreased to atmospheric pressure, the microcapsules were obtained.? Coacervation was achieved by the precipitation of poly(HDFDA) during the decrease in the pressure of CO2;the solubility of poly(HDFDA) in CO2 decreased with the pressure.? The structure and morphology of the microparticles were investigated by using a scanning electron microscope (SEM) and an electron probe microanalyzer (EPMA) equipped with a wavelength dispersive X-ray spectroscope (WDX).展开更多
The flow shop scheduling problem is important for the manufacturing industry.Effective flow shop scheduling can bring great benefits to the industry.However,there are few types of research on Distributed Hybrid Flow S...The flow shop scheduling problem is important for the manufacturing industry.Effective flow shop scheduling can bring great benefits to the industry.However,there are few types of research on Distributed Hybrid Flow Shop Problems(DHFSP)by learning assisted meta-heuristics.This work addresses a DHFSP with minimizing the maximum completion time(Makespan).First,a mathematical model is developed for the concerned DHFSP.Second,four Q-learning-assisted meta-heuristics,e.g.,genetic algorithm(GA),artificial bee colony algorithm(ABC),particle swarm optimization(PSO),and differential evolution(DE),are proposed.According to the nature of DHFSP,six local search operations are designed for finding high-quality solutions in local space.Instead of randomselection,Q-learning assists meta-heuristics in choosing the appropriate local search operations during iterations.Finally,based on 60 cases,comprehensive numerical experiments are conducted to assess the effectiveness of the proposed algorithms.The experimental results and discussions prove that using Q-learning to select appropriate local search operations is more effective than the random strategy.To verify the competitiveness of the Q-learning assistedmeta-heuristics,they are compared with the improved iterated greedy algorithm(IIG),which is also for solving DHFSP.The Friedman test is executed on the results by five algorithms.It is concluded that the performance of four Q-learning-assisted meta-heuristics are better than IIG,and the Q-learning-assisted PSO shows the best competitiveness.展开更多
Remote sensing is of great importance for analyzing and studying various phenomena occurrence and development on Earth.Today is possible to extract features specific to various fields of application with the applicati...Remote sensing is of great importance for analyzing and studying various phenomena occurrence and development on Earth.Today is possible to extract features specific to various fields of application with the application of modern machine learning techniques,such as Convolutional Neural Networks(CNN)on MultiSpectral Images(MSI).This systematic review examines the application of 1D-,2D-,3D-,and 4D-CNNs to MSI,following Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidelines.This review addresses three Research Questions(RQ):RQ1:“In which application domains different CNN models have been successfully applied for processing MSI data?”,RQ2:“What are the commonly utilized MSI datasets for training CNN models in the context of processing multispectral satellite imagery?”,and RQ3:“How does the degree of CNN complexity impact the performance of classification,regression or segmentation tasks for multispectral satellite imagery?”.Publications are selected from three databases,Web of Science,IEEE Xplore,and Scopus.Based on the obtained results,the main conclusions are:(1)The majority of studies are applied in the field of agriculture and are using Sentinel-2 satellite data;(2)Publications implementing 1D-,2D-,and 3D-CNNs mostly utilize classification.For 4D-CNN,there are limited number of studies,and all of them use segmentation;(3)This study shows that 2D-CNNs prevail in all application domains,but 3D-CNNs prove to be better for spatio-temporal pattern recognition,more specifically in agricultural and environmental monitoring applications.1D-CNNs are less common compared to 2D-CNNs and 3D-CNNs,but they show good performance in spectral analysis tasks.4D-CNNs are more complex and still underutilized,but they have potential for complex data analysis.More details about metrics according to each CNN are provided in the text and supplementary files,offering a comprehensive overview of the evaluation metrics for each type of machine learning technique applied.展开更多
The rapid and increasing growth in the volume and number of cyber threats from malware is not a real danger;the real threat lies in the obfuscation of these cyberattacks,as they constantly change their behavior,making...The rapid and increasing growth in the volume and number of cyber threats from malware is not a real danger;the real threat lies in the obfuscation of these cyberattacks,as they constantly change their behavior,making detection more difficult.Numerous researchers and developers have devoted considerable attention to this topic;however,the research field has not yet been fully saturated with high-quality studies that address these problems.For this reason,this paper presents a novel multi-objective Markov-enhanced adaptive whale optimization(MOMEAWO)cybersecurity model to improve the classification of binary and multi-class malware threats through the proposed MOMEAWO approach.The proposed MOMEAWO cybersecurity model aims to provide an innovative solution for analyzing,detecting,and classifying the behavior of obfuscated malware within their respective families.The proposed model includes three classification types:Binary classification and multi-class classification(e.g.,four families and 16 malware families).To evaluate the performance of this model,we used a recently published dataset called the Canadian Institute for Cybersecurity Malware Memory Analysis(CIC-MalMem-2022)that contains balanced data.The results show near-perfect accuracy in binary classification and high accuracy in multi-class classification compared with related work using the same dataset.展开更多
This paper addresses the problem of robust iterative learning control design for a class of uncertain multiple-input multipleoutput discrete linear systems with actuator faults. The stability theory for linear repetit...This paper addresses the problem of robust iterative learning control design for a class of uncertain multiple-input multipleoutput discrete linear systems with actuator faults. The stability theory for linear repetitive processes is used to develop formulas for gain matrices design, together with convergent conditions in terms of linear matrix inequalities. An extension to deal with model uncertainty of the polytopic or norm bounded form is also developed and an illustrative example is given.展开更多
Recently,online learning platforms have proven to help people gain knowledge more conveniently.Since the outbreak of COVID-19 in 2020,online learning has become a mainstream mode,as many schools have adopted its forma...Recently,online learning platforms have proven to help people gain knowledge more conveniently.Since the outbreak of COVID-19 in 2020,online learning has become a mainstream mode,as many schools have adopted its format.The platforms are able to capture substantial data relating to the students’learning activities,which could be analyzed to determine relationships between learning behaviors and study habits.As such,an intelligent analysis method is needed to process efficiently this high volume of information.Clustering is an effect data mining method which discover data distribution and hidden characteristic from uncharacterized online learning data.This study proposes a clustering algorithm based on brain storm optimization(CBSO)to categorize students according to their learning behaviors and determine their characteristics.This enables teaching to be tailored to taken into account those results,thereby,improving the education quality over time.Specifically,we use the individual of CBSO to represent the distribution of students and find the optimal one by the operations of convergence and divergence.The experiments are performed on the 104 students’online learning data,and the results show that CBSO is feasible and efficient.展开更多
Using time domain reflectometry (TDR),dielectric relaxation studies were carried out on binary mixtures of amides (N-methylformamide (NMF) and N,N-dimethylformamide (DMF)) with alcohols (1-butanol,1-pentanol,1-hexanol...Using time domain reflectometry (TDR),dielectric relaxation studies were carried out on binary mixtures of amides (N-methylformamide (NMF) and N,N-dimethylformamide (DMF)) with alcohols (1-butanol,1-pentanol,1-hexanol,1-heptanol,1-octanol,and 1-decanol) for various concentrations over the frequency range from 10 MHz to 10 GHz at 303 K. The Kirkwood correlation factor and excess dielectric constant properties were determined and discussed to yield information on the molecular interactions of the systems. The relaxation time varied with the chain length of alcohols and substituted amides were noticed. The Bruggeman plot shows a deviation from linearity. This deviation was attributed to some sort of molecular interaction which may take place between the alcohols and substituted amides. The excess static permittivity and excess inverse relaxation time values varied from negative to positive for all the systems indicating that the solute-solvent interaction existed between alcohols and substituted amides for all the dynamics of the mixture.展开更多
This work addresses bi-objective hybrid flow shop scheduling problems considering consistent sublots(Bi-HFSP_CS).The objectives are to minimize the makespan and total energy consumption.First,the Bi-HFSP_CS is formali...This work addresses bi-objective hybrid flow shop scheduling problems considering consistent sublots(Bi-HFSP_CS).The objectives are to minimize the makespan and total energy consumption.First,the Bi-HFSP_CS is formalized,followed by the establishment of a mathematical model.Second,enhanced version of the artificial bee colony(ABC)algorithms is proposed for tackling the Bi-HFSP_CS.Then,fourteen local search operators are employed to search for better solutions.Two different Q-learning tactics are developed to embed into the ABC algorithm to guide the selection of operators throughout the iteration process.Finally,the proposed tactics are assessed for their efficacy through a comparison of the ABC algorithm,its three variants,and three effective algorithms in resolving 95 instances of 35 different problems.The experimental results and analysis showcase that the enhanced ABC algorithm combined with Q-learning(QABC1)demonstrates as the top performer for solving concerned problems.This study introduces a novel approach to solve the Bi-HFSP_CS and illustrates its efficacy and superior competitive strength,offering beneficial perspectives for exploration and research in relevant domains.展开更多
We have been studying various types of computer-generated holograms for three-dimensional （3D） displays both for a real-time holographic video display and a hard copy, or a printed hologram. For the hard copy output...We have been studying various types of computer-generated holograms for three-dimensional （3D） displays both for a real-time holographic video display and a hard copy, or a printed hologram. For the hard copy output, we have developed a direct fringe printer, which is achieved to print over 100 gigapixels computer-generated hologram with 0.44μm pitch. In this paper, we introduce our recent progresses on the rainbow hologram, the cylindrical holograms, and the disk hologram for 3D display.展开更多
We present an engineered version of the divide-and-conquer algorithm for finding the closest pair of points, within a given set of points in the XY-plane. For this version of the algorithm we show that only two pairwi...We present an engineered version of the divide-and-conquer algorithm for finding the closest pair of points, within a given set of points in the XY-plane. For this version of the algorithm we show that only two pairwise comparisons are required in the combine step, for each point that lies in the 25-wide vertical slab. The correctness of the algorithm is shown for all Minkowski distances with p ≥ 1. We also show empirically that, although the time complexity of the algorithm is still O（n lgn）, the reduction in the total number of comparisons leads to a significant reduction in the total execution time, for inputs with size sufficiently large.展开更多
We investigate the computer-generated hologram with full parallax and which can be reconstructed with white light. The object of the hologram is processed from three-dimensional computer graphics polygon data and has ...We investigate the computer-generated hologram with full parallax and which can be reconstructed with white light. The object of the hologram is processed from three-dimensional computer graphics polygon data and has shaded surface for hidden surface removal. The optically reconstructed image from the printed hologram is evaluated.展开更多
In this study,four commercially available bio-derived epoxy systems(extracted from cashew nutshell liquid)were prepared and characterised.The glass transition temperature(Tg),dielectric spectroscopy,DC conductivity an...In this study,four commercially available bio-derived epoxy systems(extracted from cashew nutshell liquid)were prepared and characterised.The glass transition temperature(Tg),dielectric spectroscopy,DC conductivity and breakdown properties of these epoxy resins were studied.Differential scanning calorimetry(DSC)demonstrated that the T_(g) of the investigated systems ranged from 67 to 122°C.The DC conductivity was very low(<10^(-16) S cm^(-1))and comparable to the conventional dielectrics at room temperature(RT).However,all systems showed a strong temperature dependence of the electrical conductivity and exhibited sharp increase around their respective T_(g).Arrhenius analysis led to activation energy,E_(a),values around 1 eV;higher E_(a) values were observed in systems with a lower T_(g).Dielectric spectroscopy revealed a flat and low response at temperature below T_(g).However,both the real and imaginary permittivity increased with decreasing frequency at mid to low frequencies as the temperatures approached T_(g).The variations of AC breakdown strength of all samples were not statistically significant,but the DC breakdown strength of sample 2503Aþ2002B was higher than the others,which might be due to reduced charge transport in this system.The results indicate that novel bio-derived epoxy systems from renewable sources are potential alternatives for traditional petroleum-based epoxy systems in certain insulation applications.展开更多
In this paper,we present solutions for the one-dimensional coupled nonlinear Schrödinger(CNLS)equations by the Constrained Interpolation Profile-Basis Set(CIP-BS)method.This method uses a simple polynomial basis ...In this paper,we present solutions for the one-dimensional coupled nonlinear Schrödinger(CNLS)equations by the Constrained Interpolation Profile-Basis Set(CIP-BS)method.This method uses a simple polynomial basis set,by which physical quantities are approximated with their values and derivatives associated with grid points.Nonlinear operations on functions are carried out in the framework of differential algebra.Then,by introducing scalar products and requiring the residue to be orthogonal to the basis,the linear and nonlinear partial differential equations are reduced to ordinary differential equations for values and spatial derivatives.The method gives stable,less diffusive,and accurate results for the CNLS equations.展开更多
Recently,high di/dt and dv/dt switching operations of power converter circuits has been discussed for realizing a high-efficiency power converter circuit.In this case,parasitic inductances of the bus bar between a DC ...Recently,high di/dt and dv/dt switching operations of power converter circuits has been discussed for realizing a high-efficiency power converter circuit.In this case,parasitic inductances of the bus bar between a DC capacitor and power devices may cause issues of overshoot voltage and electromagnetic interference(EMI)noise.Therefore,it is necessary to design the bus bar geometry while considering the minimization and optimization of the parasitic inductance of bus bar.This paper discusses a relationship between bus bar geometry and switching characteristics.In addition,the bus bar analysis is based on the PEEC method,and the bus bar geometry is designed by considering the stray inductance with using an inductance-map method.Moreover,this paper also presents a design procedure of acceptable stray inductance based on a standardization method.It should be noted that the stray inductance is designed not for minimization,but optimization,and it is shown not as an absolute value(H),but as a percentage value(%).Finally,the oscillation waveforms under turn-off operation will be discussed depending on the bus bar geometry.展开更多
基金supported by Huck Institutes of the Life Sciences at Penn State University through the Huck Innovative and Transformational Seed Grant(HITS).
文摘Advancing 3D magnesium(Mg)development beyond current limitations requires controlling Mg alloy degradation in pre-designed,low-dimension architectures.This study reveals a mechanistic switch in the corrosion behavior of Mg alloy(3.6%Al,0.8%Zn)diamond lattice structures,induced by plasma nanosynthesis(400 eV Ar^(+)ions,fluence 1×10^(17) ions/cm^(2)).Plasma treatment of the Mg alloy increases surface Mg from 1.5%to 14.5%,enhances carbonate formation,and generates a nanostructured surface with a Mg carbonate layer over an oxide/hydroxide layer.In vitro and in vivo analyses over 8 wk demonstrate how this treatment fundamentally alters the degradation process and stability of these 3D architectures.While untreated samples initially formed a protective film that subsequently diminished,DPNS-treated samples demonstrated an inverse corrosion behavior.X-ray photoelectron spectroscopy(XPS)and electrochemical impedance spectroscopy(EIS)confirmed the presence of a stable,protective layer composed of magnesium oxide,magnesium hydroxide,and magnesium carbonate on the DPNS-treated surfaces.After 14 days,the DPNS-treated sample exhibited a more positive corrosion potential(-0.69 V versus-1.36 V)and a marginally lower current density(0.73 mA/cm^(2)compared to 0.75 mA/c^(2))relative to the control.This protective layer,combined with modified surface topology,initiated a core-to-periphery degradation pattern that maintained structural integrity for up to 8 wk post-implantation.These findings support the conclusion that the DPNS-treated scaffold demonstrates sustained improved corrosion resistance over time compared to the untreated control.Micro-CT revealed plasma-treated samples retained larger struts(504.9±95.3μm at 8 wk)and formed larger H_(2) pockets extending 14.2 mm from the implant center,versus 4.9 mm in controls.This corrosion behavior switch enhances stability but risks pore clogging,offering insights for tailoring Mg alloy degradation and H_(2) evolution in 3D architectures for biomedical applications.
基金This work was financially supported by the National Natural Science Foundation of China (No.51977114,52177020)Fundamental Research Funds for the Central Universities (No.FRF-NP-19-008 and FRF-TP-20-02B2)Scientific and Techno-logical Innovation Foundation of Foshan (BK21BE006).
文摘Recyclability and self-healing are two most critical factors in developing sustainable polymers to deal with environmental pollution and resource waste.In this work,a dynamic cross-linked polyimide insulation film with full closed-loop recyclability is successfully prepared,which also possesses good self-healing ability after being mechanical/electrical damaged depending on the Schiff base dynamic covalent bonds.The recycled and self-healed polyimide film still maintain its good tensile strength(r t)>60 MPa with Young’s modulus(E)>4 GPa,high thermal stability with glass transition temperature(T g)>220℃,and outstanding insulation property with breakdown strength(E 0)>358 kV mm^(-1),making it a very promising low energy consumption and high temperature resistant insulation material.The strategy of using Schiff base dynamic covalent bonds for reversible repairing the structure of high T g polyimides promotes the wider application of such sustainable and recyclable material in the field of electrical power and micro-electronics.
文摘Artificial intelligence and computer vision need methods for 2D （two-dimensional） shape retrieval having discrete set of boundary points. A novel method of MHR （Hurwitz-Radon Matrices） is used in shape modeling. Proposed method is based on the family of MHR which possess columns composed of orthogonal vectors. 2D curve is retrieved via different functions as probability distribution functions： sine, cosine, tangent, logarithm, exponent, arcsin, arccos, arctan and power function. Created from the family of N-1 MHR and completed with the identical matrix, system of matrices is orthogonal only for dimensions N = 2, 4 or 8. Orthogonality of columns and rows is very significant for stability and high precision of calculations. MHR method is interpolating the function point by point without using any formula of function. Main features of MHR method are： accuracy of curve reconstruction depending on number of nodes and method of choosing nodes, interpolation of L points of the curve is connected with the computational cost of rank O（L）, MHR interpolation is not a linear interpolation.
文摘This paper presents discrete wavelet transform （DWT） and its inverse （IDWT） with Haar wavelets as tools to compute the variable size interpolated versions of an image at optimum computational load. As a human observer moves closer to or farther from a scene, the retinal image of the scene zooms in or out, respectively. This zooming in or out can be modeled using variable scale interpolation. The paper proposes a novel way of applying DWT and IDWT in a piecewise manner by non-uniform down- or up-sampling of the images to achieve partially sampled versions of the images. The partially sampled versions are then aggregated to achieve the final variable scale interpolated images. The non-uniform down- or up-sampling here is a function of the required scale of interpolation. Appropriate zero padding is used to make the images suitable for the required non-uniform sampling and the subsequent interpolation to the required scale. The concept of zeroeth level DWT is introduced here, which works as the basis for interpolating the images to achieve bigger size than the original one. The main emphasis here is on the computation of variable size images at less computational load, without compromise of quality of images. The interpolated images to different sizes and the reconstructed images are benchmarked using the statistical parameters and visual comparison. It has been found that the proposed approach performs better as compared to bilinear and bicubic interpolation techniques.
文摘In past years,growing efforts have been made to the rapid interpretation of magnetic field data acquired by a sparse synthetic or real magnetic sensor array.An appealing requirement on such sparse array arranged within a specified survey region is that to make the number of sensor elements as small as possible,meanwhile without deteriorating imaging quality.For this end,we propose a novel methodology of arranging sensors in an optimal manner,exploring the concept of information capacity developed originally in the communication society.The proposed scheme reduces mathematically the design of a sparse sensor array into solving a combinatorial optimization problem,which can be resolved efficiently using widely adopted Simultaneous Perturbation and Statistical Algorithm(SPSA).Three sets of numerical examples of designing optimal sensor array are provided to demonstrate the performance of proposed methodology.
文摘Image analysis and computer vision are interested in suitable methods to solve the nonlinear equations. Coordinate x??for f (x)?= 0?is crucial because each equation can be transformed into f (x)?= 0. A novel method of Hurwitz-Radon Matrices (MHR) can be used in approximation of a root of function in the plane. The paper contains a way of data approximation via MHR method to solve any equation. Proposed method is based on the family of Hurwitz-Radon (HR) matrices. The matrices are skew-symmetric and possess columns composed of orthogonal vectors. The operator of Hurwitz-Radon (OHR), built from these matrices, is described. Two-dimensional data are represented by discrete set of curve??f points. It is shown how to create the orthogonal OHR operator and how to use it in a process of data interpolation. MHR method is interpolating the curve point by point without using any formula or function.
文摘We report a method for the coacervation micro-encapsulation of several forms of CaCO3 microparticles with the fluoropolymer poly(heptadecafluorodecyl acrylate) (poly (HDFDA)) by pressure-induced phase separation of a supercritical CO2 solution.? A suspension of CaCO3 in CO2 and dissolved poly(HDFDA) were mixed in supercritical CO2.? After the system pressure was slowly decreased to atmospheric pressure, the microcapsules were obtained.? Coacervation was achieved by the precipitation of poly(HDFDA) during the decrease in the pressure of CO2;the solubility of poly(HDFDA) in CO2 decreased with the pressure.? The structure and morphology of the microparticles were investigated by using a scanning electron microscope (SEM) and an electron probe microanalyzer (EPMA) equipped with a wavelength dispersive X-ray spectroscope (WDX).
基金partially supported by the Guangdong Basic and Applied Basic Research Foundation(2023A1515011531)the National Natural Science Foundation of China under Grant 62173356+2 种基金the Science and Technology Development Fund(FDCT),Macao SAR,under Grant 0019/2021/AZhuhai Industry-University-Research Project with Hongkong and Macao under Grant ZH22017002210014PWCthe Key Technologies for Scheduling and Optimization of Complex Distributed Manufacturing Systems(22JR10KA007).
文摘The flow shop scheduling problem is important for the manufacturing industry.Effective flow shop scheduling can bring great benefits to the industry.However,there are few types of research on Distributed Hybrid Flow Shop Problems(DHFSP)by learning assisted meta-heuristics.This work addresses a DHFSP with minimizing the maximum completion time(Makespan).First,a mathematical model is developed for the concerned DHFSP.Second,four Q-learning-assisted meta-heuristics,e.g.,genetic algorithm(GA),artificial bee colony algorithm(ABC),particle swarm optimization(PSO),and differential evolution(DE),are proposed.According to the nature of DHFSP,six local search operations are designed for finding high-quality solutions in local space.Instead of randomselection,Q-learning assists meta-heuristics in choosing the appropriate local search operations during iterations.Finally,based on 60 cases,comprehensive numerical experiments are conducted to assess the effectiveness of the proposed algorithms.The experimental results and discussions prove that using Q-learning to select appropriate local search operations is more effective than the random strategy.To verify the competitiveness of the Q-learning assistedmeta-heuristics,they are compared with the improved iterated greedy algorithm(IIG),which is also for solving DHFSP.The Friedman test is executed on the results by five algorithms.It is concluded that the performance of four Q-learning-assisted meta-heuristics are better than IIG,and the Q-learning-assisted PSO shows the best competitiveness.
基金supported through Project Coastal Auto-purification Assessment Technology(CAAT),funded by the European Union from European Structural and Investment Funds 2014–2020(No.KK.01.1.1.04.0064).
文摘Remote sensing is of great importance for analyzing and studying various phenomena occurrence and development on Earth.Today is possible to extract features specific to various fields of application with the application of modern machine learning techniques,such as Convolutional Neural Networks(CNN)on MultiSpectral Images(MSI).This systematic review examines the application of 1D-,2D-,3D-,and 4D-CNNs to MSI,following Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidelines.This review addresses three Research Questions(RQ):RQ1:“In which application domains different CNN models have been successfully applied for processing MSI data?”,RQ2:“What are the commonly utilized MSI datasets for training CNN models in the context of processing multispectral satellite imagery?”,and RQ3:“How does the degree of CNN complexity impact the performance of classification,regression or segmentation tasks for multispectral satellite imagery?”.Publications are selected from three databases,Web of Science,IEEE Xplore,and Scopus.Based on the obtained results,the main conclusions are:(1)The majority of studies are applied in the field of agriculture and are using Sentinel-2 satellite data;(2)Publications implementing 1D-,2D-,and 3D-CNNs mostly utilize classification.For 4D-CNN,there are limited number of studies,and all of them use segmentation;(3)This study shows that 2D-CNNs prevail in all application domains,but 3D-CNNs prove to be better for spatio-temporal pattern recognition,more specifically in agricultural and environmental monitoring applications.1D-CNNs are less common compared to 2D-CNNs and 3D-CNNs,but they show good performance in spectral analysis tasks.4D-CNNs are more complex and still underutilized,but they have potential for complex data analysis.More details about metrics according to each CNN are provided in the text and supplementary files,offering a comprehensive overview of the evaluation metrics for each type of machine learning technique applied.
文摘The rapid and increasing growth in the volume and number of cyber threats from malware is not a real danger;the real threat lies in the obfuscation of these cyberattacks,as they constantly change their behavior,making detection more difficult.Numerous researchers and developers have devoted considerable attention to this topic;however,the research field has not yet been fully saturated with high-quality studies that address these problems.For this reason,this paper presents a novel multi-objective Markov-enhanced adaptive whale optimization(MOMEAWO)cybersecurity model to improve the classification of binary and multi-class malware threats through the proposed MOMEAWO approach.The proposed MOMEAWO cybersecurity model aims to provide an innovative solution for analyzing,detecting,and classifying the behavior of obfuscated malware within their respective families.The proposed model includes three classification types:Binary classification and multi-class classification(e.g.,four families and 16 malware families).To evaluate the performance of this model,we used a recently published dataset called the Canadian Institute for Cybersecurity Malware Memory Analysis(CIC-MalMem-2022)that contains balanced data.The results show near-perfect accuracy in binary classification and high accuracy in multi-class classification compared with related work using the same dataset.
基金supported by National Natural Science Foundation of China(Nos.61273070 and 61203092)111 project(No.B12018)
文摘This paper addresses the problem of robust iterative learning control design for a class of uncertain multiple-input multipleoutput discrete linear systems with actuator faults. The stability theory for linear repetitive processes is used to develop formulas for gain matrices design, together with convergent conditions in terms of linear matrix inequalities. An extension to deal with model uncertainty of the polytopic or norm bounded form is also developed and an illustrative example is given.
基金This work was partially supported by the National Natural Science Foundation of China(61876089,61876185,61902281,61375121)the Opening Project of Jiangsu Key Laboratory of Data Science and Smart Software(No.2019DS301)+1 种基金the Engineering Research Center of Digital Forensics,Ministry of Education,the Key Research and Development Program of Jiangsu Province(BE2020633)the Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘Recently,online learning platforms have proven to help people gain knowledge more conveniently.Since the outbreak of COVID-19 in 2020,online learning has become a mainstream mode,as many schools have adopted its format.The platforms are able to capture substantial data relating to the students’learning activities,which could be analyzed to determine relationships between learning behaviors and study habits.As such,an intelligent analysis method is needed to process efficiently this high volume of information.Clustering is an effect data mining method which discover data distribution and hidden characteristic from uncharacterized online learning data.This study proposes a clustering algorithm based on brain storm optimization(CBSO)to categorize students according to their learning behaviors and determine their characteristics.This enables teaching to be tailored to taken into account those results,thereby,improving the education quality over time.Specifically,we use the individual of CBSO to represent the distribution of students and find the optimal one by the operations of convergence and divergence.The experiments are performed on the 104 students’online learning data,and the results show that CBSO is feasible and efficient.
文摘Using time domain reflectometry (TDR),dielectric relaxation studies were carried out on binary mixtures of amides (N-methylformamide (NMF) and N,N-dimethylformamide (DMF)) with alcohols (1-butanol,1-pentanol,1-hexanol,1-heptanol,1-octanol,and 1-decanol) for various concentrations over the frequency range from 10 MHz to 10 GHz at 303 K. The Kirkwood correlation factor and excess dielectric constant properties were determined and discussed to yield information on the molecular interactions of the systems. The relaxation time varied with the chain length of alcohols and substituted amides were noticed. The Bruggeman plot shows a deviation from linearity. This deviation was attributed to some sort of molecular interaction which may take place between the alcohols and substituted amides. The excess static permittivity and excess inverse relaxation time values varied from negative to positive for all the systems indicating that the solute-solvent interaction existed between alcohols and substituted amides for all the dynamics of the mixture.
基金supported by the National Natural Science Foundation of China(No.62173356)Science and Technology Development Fund(FDCT),Macao SAR(No.0019/2021/A)+2 种基金Zhuhai Industry-University-Research Project with Hongkong and Macao(No.ZH22017002210014PWC)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515011531)Key Technologies for Scheduling and Optimization of Complex Distributed Manufacturing Systems(No.22JR10KA007).
文摘This work addresses bi-objective hybrid flow shop scheduling problems considering consistent sublots(Bi-HFSP_CS).The objectives are to minimize the makespan and total energy consumption.First,the Bi-HFSP_CS is formalized,followed by the establishment of a mathematical model.Second,enhanced version of the artificial bee colony(ABC)algorithms is proposed for tackling the Bi-HFSP_CS.Then,fourteen local search operators are employed to search for better solutions.Two different Q-learning tactics are developed to embed into the ABC algorithm to guide the selection of operators throughout the iteration process.Finally,the proposed tactics are assessed for their efficacy through a comparison of the ABC algorithm,its three variants,and three effective algorithms in resolving 95 instances of 35 different problems.The experimental results and analysis showcase that the enhanced ABC algorithm combined with Q-learning(QABC1)demonstrates as the top performer for solving concerned problems.This study introduces a novel approach to solve the Bi-HFSP_CS and illustrates its efficacy and superior competitive strength,offering beneficial perspectives for exploration and research in relevant domains.
基金A part of this work was supported by JSPS KAKENHI21760265
文摘We have been studying various types of computer-generated holograms for three-dimensional （3D） displays both for a real-time holographic video display and a hard copy, or a printed hologram. For the hard copy output, we have developed a direct fringe printer, which is achieved to print over 100 gigapixels computer-generated hologram with 0.44μm pitch. In this paper, we introduce our recent progresses on the rainbow hologram, the cylindrical holograms, and the disk hologram for 3D display.
文摘We present an engineered version of the divide-and-conquer algorithm for finding the closest pair of points, within a given set of points in the XY-plane. For this version of the algorithm we show that only two pairwise comparisons are required in the combine step, for each point that lies in the 25-wide vertical slab. The correctness of the algorithm is shown for all Minkowski distances with p ≥ 1. We also show empirically that, although the time complexity of the algorithm is still O（n lgn）, the reduction in the total number of comparisons leads to a significant reduction in the total execution time, for inputs with size sufficiently large.
基金supported by the Futaba Electronics Memorial Foundation
文摘We investigate the computer-generated hologram with full parallax and which can be reconstructed with white light. The object of the hologram is processed from three-dimensional computer graphics polygon data and has shaded surface for hidden surface removal. The optically reconstructed image from the printed hologram is evaluated.
文摘In this study,four commercially available bio-derived epoxy systems(extracted from cashew nutshell liquid)were prepared and characterised.The glass transition temperature(Tg),dielectric spectroscopy,DC conductivity and breakdown properties of these epoxy resins were studied.Differential scanning calorimetry(DSC)demonstrated that the T_(g) of the investigated systems ranged from 67 to 122°C.The DC conductivity was very low(<10^(-16) S cm^(-1))and comparable to the conventional dielectrics at room temperature(RT).However,all systems showed a strong temperature dependence of the electrical conductivity and exhibited sharp increase around their respective T_(g).Arrhenius analysis led to activation energy,E_(a),values around 1 eV;higher E_(a) values were observed in systems with a lower T_(g).Dielectric spectroscopy revealed a flat and low response at temperature below T_(g).However,both the real and imaginary permittivity increased with decreasing frequency at mid to low frequencies as the temperatures approached T_(g).The variations of AC breakdown strength of all samples were not statistically significant,but the DC breakdown strength of sample 2503Aþ2002B was higher than the others,which might be due to reduced charge transport in this system.The results indicate that novel bio-derived epoxy systems from renewable sources are potential alternatives for traditional petroleum-based epoxy systems in certain insulation applications.
文摘In this paper,we present solutions for the one-dimensional coupled nonlinear Schrödinger(CNLS)equations by the Constrained Interpolation Profile-Basis Set(CIP-BS)method.This method uses a simple polynomial basis set,by which physical quantities are approximated with their values and derivatives associated with grid points.Nonlinear operations on functions are carried out in the framework of differential algebra.Then,by introducing scalar products and requiring the residue to be orthogonal to the basis,the linear and nonlinear partial differential equations are reduced to ordinary differential equations for values and spatial derivatives.The method gives stable,less diffusive,and accurate results for the CNLS equations.
文摘Recently,high di/dt and dv/dt switching operations of power converter circuits has been discussed for realizing a high-efficiency power converter circuit.In this case,parasitic inductances of the bus bar between a DC capacitor and power devices may cause issues of overshoot voltage and electromagnetic interference(EMI)noise.Therefore,it is necessary to design the bus bar geometry while considering the minimization and optimization of the parasitic inductance of bus bar.This paper discusses a relationship between bus bar geometry and switching characteristics.In addition,the bus bar analysis is based on the PEEC method,and the bus bar geometry is designed by considering the stray inductance with using an inductance-map method.Moreover,this paper also presents a design procedure of acceptable stray inductance based on a standardization method.It should be noted that the stray inductance is designed not for minimization,but optimization,and it is shown not as an absolute value(H),but as a percentage value(%).Finally,the oscillation waveforms under turn-off operation will be discussed depending on the bus bar geometry.
