Identification of various food residuals on denim based on hyperspectral imaging system and combination optimal strategy

As the science and technology develop,crime methods and scenes have become increasingly complex and diverse.Trace evidence analysis has become amore and more important criminal investigation technology and liquid is the main form of trace evidence.Food can provide not only energy,but clues to solve crimes.In this study,we build a hyperspectral imaging system to detect liquid residue traces,including apple juice,coffee,cola,milk and tea,on denims with light,middle and dark colors.The obtained hyperspectral images are first subjected to spectral calibration and hyperspectral data pretreatment.Subsequently,Partial Least Squares(PLS)is applied to select the informative wavelengths from the preprocessed spectra.For modeling phase,the combination optimal strategy,support vector machine(SVM)combined with random forest(RF),is developed to establish classification models.The experimental results demonstrate that the combination optimal model can achieve TPR,FPR,Precision,Recall,F1,and AUC of 83.5%,2.30%,79.7%,83.5%,81.6%,and 94.7%for classifying fabrics contaminated by various food residuals.With respect to the classification of liquid and fabric types,the combination optimalmodel also yields satisfactory classification performance.In future work,wewill expand the types of liquid,and make appropriate adjustment to algorithms for improving the robustness of classification models.This research may play a positive role in the construction of a harmonious society.

Prediction of a maximum pull-out load of anchor bolts using an optimal combination model

The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived using the optimally weighted combination theory and the minimum sum of logarithmic squared errors as the objective function.Two typical anchor bolt pull-out engineering cases were selected to compare the performance of the proposed model with those of existing ones.Results showed that the optimal combination model was suitable not only for the slow P-s curve but also for the steep P-s curve.Its accuracy and stable reliability,as well as its prediction capability classification,were better than those of the other prediction models.Therefore,the optimal combination model is an effective processing method for predicting the maximum pull-out load of anchor bolts according to measured data.

A Subdivision-Based Combined Shape and Topology Optimization in Acoustics

We propose a combined shape and topology optimization approach in this research for 3D acoustics by using the isogeometric boundary element method with subdivision surfaces.The existing structural optimization methods mainly contain shape and topology schemes,with the former changing the surface geometric profile of the structure and the latter changing thematerial distribution topology or hole topology of the structure.In the present acoustic performance optimization,the coordinates of the control points in the subdivision surfaces fine mesh are selected as the shape design parameters of the structure,the artificial density of the sound absorbing material covered on the structure surface is set as the topology design parameter,and the combined topology and shape optimization approach is established through the sound field analysis of the subdivision surfaces boundary element method as a bridge.The topology and shape sensitivities of the approach are calculated using the adjoint variable method,which ensures the efficiency of the optimization.The geometric jaggedness and material distribution discontinuities that appear in the optimization process are overcome to a certain degree by the multiresolution method and solid isotropic material with penalization.Numerical examples are given to validate the effectiveness of the presented optimization approach.

Numerical simulation and combination optimization of aluminum holding furnace linings based on simulated annealing

To reduce heat loss and save cost, a combination decision model of reverb aluminum holding furnace linings in aluminum casting industry was established based on economic thickness method, and was resolved using simulated annealing. Meanwhile, a three-dimensional mathematical model of aluminum holding furnace linings was developed and integrated with user-defined heat load distribution regime model. The optimal combination was as follows: side wall with 80 mm alumino-silicate fiber felts, 232 mm diatomite brick and 116 mm chamotte brick; top wall with 50 mm clay castables, 110 mm alumino-silicate fiber felts and 200 mm refractory concrete;and bottom wall with 232 mm high-alumina brick, 60 mm clay castables and 68 mm diatomite brick. Lining temperature from high to low was successively bottom wall, side wall, and top wall. Lining temperature gradient in increasing order of magnitude was refractory layer and insulation layer. It was indicated that the results of combination optimization of aluminum holding furnace linings were valid and feasible, and its thermo-physical mechanism and cost characteristics were reasonably revealed.

Optimize the combination regimen of Trastuzumab and Nab-paclitaxel in HER2-positive tumors via modulating Caveolin-1 expression by lovastatin

The combination regimen of trastuzumab(Tras)plus Nab-paclitaxel(Nab)is recommended to treat HER2-positive(HER2+)cancers.However,they exert effects in different mechanisms:Tras need to stay on cell membranes,while Nab need to be endocytosed,therefore the concurrent combination regimen may not be the best one in HER2+tumors treatment.Caveolin-1(Cav-1)is a key player in mediating their endocytosis and is associated with their efficacy,but few researches noticed the opposite effect of Cav-1 expression on the combination efficacy.Herein,we systematically studied the Cav-1 expression level on the combination efficacy and proposed an optimized and clinically feasible combination regimen for HER2+Cav-1 High tumor treatment.In the regimen,lovastatin(Lova)was introduced to modulate the Cav-1 expression and the results indicated that Lova could downregulate Cav-1 expression,increase Tras retention on cell membrane and enhance the in vitro cytotoxicity of Tras in HER2+Cav-1 High cells but not in HER2+Cav-1 Low cells.Therefore,by exchanging the dosing sequence of Nab and Tras,and by adding Lova at appropriate time points,the precise three-drug-sequential regimen(PTDS,Nab(D1)-Lova(D2)-Lova&Tras(D2+12 h))was established.Compared with the concurrent regimen,the PTDS regimen exhibited a higher in vitro cytotoxicity and a stronger tumor growth inhibition in HER2+Cav-1 High tumors,which might be a promising combination regimen for these patients in clinics.

APPLICATION RESEARCH OF COMBINATION PRINCIPLE IN CAD FEATURE RECOGNIZATION

The method of extracting the basic features of part from the file of STEPAP214 of 3-D model is proposed. All faces in the file are the minimal elements. The combination isdone for the faces with geometry restrictions and some attributes by the theory of the bestalphabetic tree which is constructed by HU--TUCKER algorithm in combination principle. So the basicfeatures could be attained. This provides the research basis to the more share and integration ofCAD information in the virtual enterprises. Finally, a case is used to illustrate the validity ofthe approach.

OPTIMAL COMBINING PREDICTION FOR BLENDING EFFICIENCY

By means of analysing the mechanism of blending materials,a general blending efficiency model was proposed.Applying this general model to an example 9 a suitable formula of blending efficiency which is more accurate than those in papers[2-3]was obtained.Finally,a high-precision optimal combining prediction formula for calculating blending efficiency was proposed.

Study on the Optimized Combination and Utilization of Waste Resources of Agriculture and Animal Husbandry in Tibet

With the high-quality development of modern agriculture and animal husbandry in the plateau,the waste resources produced by agriculture and animal husbandry show a trend of diversification.How to effectively carry out the key work based on the optimal combination and utilization of waste resources of agriculture and animal husbandry in Tibet is imminent.To realize efficient recycling of waste resources of agriculture and animal husbandry,innovative mode is explored.On the theoretical basis,it can effectively alleviate the resource crisis,control the pollution sources,effectively utilize the resources and construct the recycling mode,which plays an important role in promoting,integrating and coordinating the high-quality development of modern agriculture and animal husbandry in the plateau.In this paper,optimal combination and utilization manner of waste resources of agriculture and animal husbandry under the circular development concept is comprehensively analyzed and summarized,to continuously improve reasonable and effective utilization level and efficiency of agricultural waste resources.It could not only inhibit waste pollution but also promote rational and effective utilization of resources,thereby laying theoretical basis for sustainable and efficient development of agriculture and animal husbandry in Tibet,promoting the improvement of agricultural and rural ecological environment,and providing the thinking for exploring model of ecological recycling in plateau.

Survey of the research on dynamic weapon-target assignment problem

The basic concepts and models of weapon-target assignment （WTA） are introduced and the mathematical nature of the WTA models is also analyzed. A systematic survey of research on WTA problem is provided. The present research on WTA is focused on models and algorithms. In the research on models of WTA, the static WTA models are mainly studied and the dynamic WTA models are not fully studied in deed. In the research on algorithms of WTA, the intelligent algorithms are often used to solve the WTA problem. The small scale of static WTA problems has been solved very well, however, the large scale of dynamic WTA problems has not been solved effectively so far. Finally, the characteristics of dynamic WTA are analyzed and directions for the future research on dynamic WTA are discussed.

Novel algorithm for constructing support vector machine regression ensemble

A novel algorithm for constructing support vector machine regression ensemble is proposed. As to regression prediction, support vector machine regression （SVMR） ensemble is proposed by resampling from given training data sets repeatedly and aggregating several independent SVMRs, each of which is trained to use a replicated training set. After training, several independently trained SVMRs need to be aggregated in an appropriate combination manner. Generally, the linear weighting is usually used like expert weighting score in Boosting Regression and it is without optimization capacity. Three combination techniques are proposed, including simple arithmetic mean, linear least square error weighting and nonlinear hierarchical combining that uses another upper-layer SVMR to combine several lower-layer SVMRs. Finally, simulation experiments demonstrate the accuracy and validity of the presented algorithm.

Developing high-efficiency base editors by combining optimized synergistic core components with new types of nuclear localization signal peptide

The clustered regularly interspaced short palindromic repeats(CRISPR)–CRISPR-associated protein(Cas) system has been widely used for genome editing. In this system, the cytosine base editor(CBE) and adenine base editor(ABE) allow generating precise and irreversible base mutations in a programmable manner and have been used in many different types of cells and organisms. However, their applications are limited by low editing efficiency at certain genomic target sites or at specific target cytosine(C) or adenine(A) residues. Using a strategy of combining optimized synergistic core components, we developed a new multiplex super-assembled ABE(sABE) in rice that showed higher base-editing efficiency than previously developed ABEs. We also designed a new type of nuclear localization signal(NLS) comprising a FLAG epitope tag with four copies of a codon-optimized NLS(F4NLS^(r2)) to generate another ABE named F4NLS-sABE. This new NLS increased editing efficiency or edited additional A at several target sites. A new multiplex super-assembled CBE(sCBE) and F4NLS^(r2) involved F4NLS-sCBE were also created using the same strategy. F4NLS-sCBE was proven to be much more efficient than sCBE in rice. These optimized base editors will serve as powerful genome-editing tools for basic research or molecular breeding in rice and will provide a reference for the development of superior editing tools for other plants or animals.

High-voltage output triboelectric nanogenerator with DC/AC optimal combination method

The high-voltage power source is one of the important research directions of triboelectric nanogenerator(TENG).In this paper,a high-voltage output TENG(HVO-TENG)is proposed with direct current/alternating current(DC/AC)optimal combination method for wind energy harvesting.Through the optimal design of a direct current generation unit(DCGU)and an alternating current generation unit(ACGU),the HVO-TENG can produce DC voltage of 21.5 kV and AC voltage of 200 V,simultaneously.The HVOTENG can continuously illuminate more than 6,000 light emitting diodes(LEDs),which is enough to drive more possible applications of TENG.Besides,this paper explored application experiments on HVO-TENG.Demonstrative experiments indicate that the high-voltage DC output is used for producing ozone,while the AC output can light up ultraviolet(UV)LEDs.The HVOTENG can increase the ozone concentration(C)in an airtight container to 3 parts per million(ppm)after 7 h and continuously light up UV LEDs.All these demonstrations verify that the HVO-TENG has important guiding significance for designing high performance TENG.

A multiple heterogeneous UAVs reconnaissance mission planning and re-planning algorithm

Reconnaissance mission planning of multiple unmanned aerial vehicles(UAVs)under an adversarial environment is a discrete combinatorial optimization problem which is proved to be a non-deterministic polynomial(NP)-complete problem.The purpose of this study is to research intelligent multiUAVs reconnaissance mission planning and online re-planning algorithm under various constraints in mission areas.For numerous targets scattered in the wide area,a reconnaissance mission planning and re-planning system is established,which includes five modules,including intelligence analysis,sub-mission area division,mission sequence planning,path smoothing,and online re-planning.The intelligence analysis module depicts the attribute of targets and the heterogeneous characteristic of UAVs and computes the number of sub-mission areas on consideration of voyage distance constraints.In the sub-mission area division module,an improved K-means clustering algorithm is designed to divide the reconnaissance mission area into several sub-mission areas,and each sub-mission is detected by the UAV loaded with various detective sensors.To control reconnaissance cost,the sampling and iteration algorithms are proposed in the mission sequence planning module,which are utilized to solve the optimal or approximately optimal reconnaissance sequence.In the path smoothing module,the Dubins curve is applied to smooth the flight path,which assure the availability of the planned path.Furthermore,an online re-planning algorithm is designed for the uncertain factor that the UAV is damaged.Finally,reconnaissance planning and re-planning experiment results show that the algorithm proposed in this paper are effective and the algorithms designed for sequence planning have a great advantage in solving efficiency and optimality.

A Combined Shape and Topology Optimization Based on Isogeometric Boundary Element Method for 3D Acoustics

A combined shape and topology optimization algorithm based on isogeometric boundary element method for 3D acoustics is developed in this study.The key treatment involves using adjoint variable method in shape sensitivity analysis with respect to non-uniform rational basis splines control points,and in topology sensitivity analysis with respect to the artificial densities of sound absorption material.OpenMP tool in Fortran code is adopted to improve the efficiency of analysis.To consider the features and efficiencies of the two types of optimization methods,this study adopts a combined iteration scheme for the optimization process to investigate the simultaneous change of geometry shape and distribution of material to achieve better noise control.Numerical examples,such as sound barrier,simple tank,and BeTSSi submarine,are performed to validate the advantage of combined optimization in noise reduction,and to demonstrate the potential of the proposed method for engineering problems.

Grey series time-delay predicting model in state estimation for power distribution networks

A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorithm of system identification, which can gradually forget past information. The grey series part of the model uses an equal dimension new information model (EDNIM) and it applies 3 points smoothing method to preprocess the original data and modify remnant difference by GM(1,1). Through the optimization of the coefficient of the model, we are able to minimize the error variance of predictive data. A case study shows that the proposed method achieved high calculation precision and speed and it can be used to obtain the predictive value in real time state estimation of power distribution networks.

STUDY ON THE METEOROLOGICAL PREDICTION MODEL USING THE LEARNING ALGORITHM OF NEURAL ENSEMBLE BASED ON PSO ALGORITHMS

Because of the difficulty in deciding on the structure of BP neural network in operational meteorological application and the tendency for the network to transform to an issue of local solution, a hybrid Particle Swarm Optimization Algorithm based on Artificial Neural Network (PSO-BP) model is proposed for monthly mean rainfall of the whole area of Guangxi. It combines Particle Swarm Optimization (PSO) with BP, that is, the number of hidden nodes and connection weights are optimized by the implementation of PSO operation. The method produces a better network architecture and initial connection weights, trains the traditional backward propagation again by training samples. The ensemble strategy is carried out for the linear programming to calculate the best weights based on the "east sum of the error absolute value" as the optimal rule. The weighted coefficient of each ensemble individual is obtained. The results show that the method can effectively improve learning and generalization ability of the neural network.

Ice concentration assimilation in a regional ice-ocean coupled model and its application in sea ice forecasting

A reasonable initial state of ice concentration is essential for accurate short-term forecasts of sea ice using ice-ocean coupled models. In this study, sea ice concentration data are assimilated into an operational ice forecast system based on a com- bined optimal interpolation and nudging scheme. The scheme produces a modeled sea ice concentration at every time step, based on the difference between observational and forecast data and on the ratio of observational error to modeled error. The impact and the effectiveness of data assimilation are investigated. Significant improvements to predictions of sea ice extent were obtained through the assimilation of ice concentration, and minor improvements through the adjustment of the upper ocean properties. The assimilation of ice thickness data did not significantly improve predictions. Forecast experiments show that the forecast accuracy is higher in summer, and that the errors on five-day forecasts occur mainly around the marginal ice zone.

Coupling model and optimal combination scheme of water,fertilizer,dissolved oxygen and temperature in greenhouse tomato under drip irrigation

Water-fertilizer coupling technology has been widely used in the world.Poor soil aeration,low temperature or high temperature can affect the rate of nutrient uptake by crop roots.Aiming at the interaction between water,fertilizer,dissolved oxygen and temperature(WFOT)coupling model and irrigation flux of tomato in greenhouse,using these four factors with a five-level uniform-precision rotatable central composite design,a mathematical model was established among the four factors affecting tomato yield in a greenhouse,and the optimal combination scheme of WFOT was obtained.Within the test range,tomato yields increased with increasing irrigation quotas(X_(1)),fertilization amount(X_(2)),dissolved oxygen(X_(3))and geothermal pipe water temperature(X_(4)).The magnitude of the effect of each factor of WFOT on tomato yield was in the following order:X_(1),X_(2),X_(4),X_(3)(spring and summer),and X_(1),X_(3),X_(2),X_(4)(autumn and winter).The interaction between high water-low heat and low water-high heat were beneficial for yield increase(spring and summer),the high fertilizer-low heat and low fertilizer-high heat interactions were beneficial to yield increase(autumn and winter).If WFOT agronomic measures were adopted according to the 95%confidence interval,there was a 95%probability that the spring-summer tomato yield will be higher than 89902 kg/hm^(2).The WFOT coupling scheme was X_(1)of 4808-5091 m3/hm^(2),X_(2)(N-P_(2)O_(5)-K_(2)O)of 171-57-84 to 186-62-89 kg/hm^(2),X_(3)of 7.9-8.2 mg/L,and X_(4)of 34.9°C-37.0°C.There was a 95%probability of tomato yield higher than 85209 kg/hm^(2)in autumn and winter,and the WFOT coupling scheme was X_(1)of 5270-5416 m3/hm^(2),X_(2)(N-P_(2)O_(5)-K_(2)O)of 151-50-76 to 167-56-82 kg/hm^(2),X_(3)of 8.0-8.2 mg/L,and X_(4)of 34.1°C-36.2°C.Overall,and the model had a very good simulation effect,with application value.The relative error between spring-summer and autumn-winter yields ranged from 1.12%to 25.34%.The results of the study can provide a theoretical basis for improving the quality and efficiency of greenhouse tomatoes.

Enhanced ants system and its application

NP-hard combinational optimization problem is not solved very well until now. One enhanced ants system based on ants system is advanced after analysis of the deficiencies of existing ants systems. Some improvements are made in state transfer rule and local modification rule. Furthermore, the enhanced ants system can solve NP-hard combinational optimization problem with restraints and condition path. The successful application of TSP problem and transportation net problem indicates that the proposed system has stronger function and higher efficiency than the original system.

Gradient Gene Algorithm: a Fast Optimization Method to MST Problem

The extension of Minimum Spanning Tree(MST) problem is an NP hard problem which does not exit a polynomial time algorithm. In this paper, a fast optimization method on MST problem——the Gradient Gene Algorithm is introduced. Compared with other evolutionary algorithms on MST problem, it is more advanced: firstly, very simple and easy to realize; then, efficient and accurate; finally general on other combination optimization problems.