While automatic image captioning systems have made notable progress in the past few years,generating captions that fully convey sentiment remains a considerable challenge.Although existing models achieve strong perfor...While automatic image captioning systems have made notable progress in the past few years,generating captions that fully convey sentiment remains a considerable challenge.Although existing models achieve strong performance in visual recognition and factual description,they often fail to account for the emotional context that is naturally present in human-generated captions.To address this gap,we propose the Sentiment-Driven Caption Generator(SDCG),which combines transformer-based visual and textual processing withmulti-level fusion.RoBERTa is used for extracting sentiment from textual input,while visual features are handled by the Vision Transformer(ViT).These features are fused using several fusion approaches,including Concatenation,Attention,Visual-Sentiment Co-Attention(VSCA),and Cross-Attention.Our experiments demonstrate that SDCG significantly outperforms baseline models such as the Generalized Image Transformer(GIT),which achieves 82.01%,and Bootstrapping Language-Image Pre-training(BLIP),which achieves 83.07%,in sentiment accuracy.While SDCG achieves 94.52%sentiment accuracy and improves scores in BLEU and ROUGE-L,the model demonstrates clear advantages.More importantly,the captions aremore natural,as they incorporate emotional cues and contextual awareness,making them resemble those written by a human.展开更多
Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(...Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(FIR)”method for multi-sourced depth data fusion,and used it to merge the electronic nautical chart dataset(referred to as Chart2014 in this paper)with the global digital elevation dataset(referred to as Globalbath2002 in this paper).Compared to the traditional fusion of two datasets by direct combination and interpolation,the new Grid-DEM formed by FIR can better represent the data characteristics of Chart2014,reduce the calculation difficulty,and be more intuitive,and,the choice of different interpolation methods in FIR and the influence of the“exclusion radius R”parameter were discussed.FIR avoids complex calculations of spatial distances among points from different sources,and instead uses spatial exclusion map to perform one-step screening based on the exclusion radius R,which greatly improved the fusion status of a reliable dataset.The fusion results of different experiments were analyzed statistically with root mean square error and mean relative error,showing that the interpolation methods based on Delaunay triangulation are more suitable for the fusion of nautical chart depth of China,and factors such as the point density distribution of multiple source data,accuracy,interpolation method,and various terrain conditions should be fully considered when selecting the exclusion radius R.展开更多
The accurate estimation of parameters is the premise for establishing a high-fidelity simulation model of a valve-controlled cylinder system.Bench test data are easily obtained,but it is challenging to emulate actual ...The accurate estimation of parameters is the premise for establishing a high-fidelity simulation model of a valve-controlled cylinder system.Bench test data are easily obtained,but it is challenging to emulate actual loads in the research on parameter estimation of valve-controlled cylinder system.Despite the actual load information contained in the operating data of the control valve,its acquisition remains challenging.This paper proposes a method that fuses bench test and operating data for parameter estimation to address the aforementioned problems.The proposed method is based on Bayesian theory,and its core is a pool fusion of prior information from bench test and operating data.Firstly,a system model is established,and the parameters in the model are analysed.Secondly,the bench and operating data of the system are collected.Then,the model parameters and weight coefficients are estimated using the data fusion method.Finally,the estimated effects of the data fusion method,Bayesian method,and particle swarm optimisation(PSO)algorithm on system model parameters are compared.The research shows that the weight coefficient represents the contribution of different prior information to the parameter estimation result.The effect of parameter estimation based on the data fusion method is better than that of the Bayesian method and the PSO algorithm.Increasing load complexity leads to a decrease in model accuracy,highlighting the crucial role of the data fusion method in parameter estimation studies.展开更多
Refined 3D modeling of mine slopes is pivotal for precise prediction of geological hazards.Aiming at the inadequacy of existing single modeling methods in comprehensively representing the overall and localized charact...Refined 3D modeling of mine slopes is pivotal for precise prediction of geological hazards.Aiming at the inadequacy of existing single modeling methods in comprehensively representing the overall and localized characteristics of mining slopes,this study introduces a new method that fuses model data from Unmanned aerial vehicles(UAV)tilt photogrammetry and 3D laser scanning through a data alignment algorithm based on control points.First,the mini batch K-Medoids algorithm is utilized to cluster the point cloud data from ground 3D laser scanning.Then,the elbow rule is applied to determine the optimal cluster number(K0),and the feature points are extracted.Next,the nearest neighbor point algorithm is employed to match the feature points obtained from UAV tilt photogrammetry,and the internal point coordinates are adjusted through the distanceweighted average to construct a 3D model.Finally,by integrating an engineering case study,the K0 value is determined to be 8,with a matching accuracy between the two model datasets ranging from 0.0669 to 1.0373 mm.Therefore,compared with the modeling method utilizing K-medoids clustering algorithm,the new modeling method significantly enhances the computational efficiency,the accuracy of selecting the optimal number of feature points in 3D laser scanning,and the precision of the 3D model derived from UAV tilt photogrammetry.This method provides a research foundation for constructing mine slope model.展开更多
Human posture estimation is a prominent research topic in the fields of human-com-puter interaction,motion recognition,and other intelligent applications.However,achieving highaccuracy in key point localization,which ...Human posture estimation is a prominent research topic in the fields of human-com-puter interaction,motion recognition,and other intelligent applications.However,achieving highaccuracy in key point localization,which is crucial for intelligent applications,contradicts the lowdetection accuracy of human posture detection models in practical scenarios.To address this issue,a human pose estimation network called AT-HRNet has been proposed,which combines convolu-tional self-attention and cross-dimensional feature transformation.AT-HRNet captures significantfeature information from various regions in an adaptive manner,aggregating them through convolu-tional operations within the local receptive domain.The residual structures TripNeck and Trip-Block of the high-resolution network are designed to further refine the key point locations,wherethe attention weight is adjusted by a cross-dimensional interaction to obtain more features.To vali-date the effectiveness of this network,AT-HRNet was evaluated using the COCO2017 dataset.Theresults show that AT-HRNet outperforms HRNet by improving 3.2%in mAP,4.0%in AP75,and3.9%in AP^(M).This suggests that AT-HRNet can offer more beneficial solutions for human posture estimation.展开更多
The development of network and information technology has brought changes to the production environment of scientific and technological information,leading to the integration of multi-type scien-tific and technologica...The development of network and information technology has brought changes to the production environment of scientific and technological information,leading to the integration of multi-type scien-tific and technological information,which has become one of the primary research focuses in the cur-rent field of scientific and technological information analysis.This article proposes a basic mode to realize the fusion of multi-type scientific and technological information,expounds the corresponding basic construction method,and applies it to the scientific and technological topics identification in the field of artificial intelligence(AI).The research results show that the multi-type scientific and technological information fusion mode proposed in this article has certain feasibility in specific appli-cation scenarios,which lays a foundation for the subsequent research work.展开更多
The control rod drive mechanism(CRDM)is an essential part of the control and safety protection system of pressurized water reactors.Current CRDM simulations are mostly performed collectively using a single method,igno...The control rod drive mechanism(CRDM)is an essential part of the control and safety protection system of pressurized water reactors.Current CRDM simulations are mostly performed collectively using a single method,ignoring the influence of multiple motion units and the differences in various features among them,which strongly affect the efficiency and accuracy of the simulations.In this study,we constructed a flow field fusion simulation method based on model features by combining key motion unit analysis and various simulation methods and then applied the method to the CRDM simulation process.CRDM performs motion unit decomposition through the structural hierarchy of function-movement-action method,and the key meta-actions are identified as the nodes in the flow field simulation.We established a fused feature-based multimethod simulation process and processed the simulation methods and data according to the features of the fluid domain space and the structural complexity to obtain the fusion simulation results.Compared to traditional simulation methods and real measurements,the simulation method provides advantages in terms of simulation efficiency and accuracy.展开更多
Weighted fusion algorithms, which can be applied in the area of multi-sensor data fusion, are advanced based on weighted least square method. A weighted fusion algorithm, in which the relationship between weight coeff...Weighted fusion algorithms, which can be applied in the area of multi-sensor data fusion, are advanced based on weighted least square method. A weighted fusion algorithm, in which the relationship between weight coefficients and measurement noise is established, is proposed by giving attention to the correlation of measurement noise. Then a simplified weighted fusion algorithm is deduced on the assumption that measurement noise is uncorrelated. In addition, an algorithm, which can adjust the weight coefficients in the simplified algorithm by making estimations of measurement noise from measurements, is presented. It is proved by emulation and experiment that the precision performance of the multi-sensor system based on these algorithms is better than that of the multi-sensor system based on other algorithms.展开更多
A key step is to extract valid information region in the fusion of multi-voltage X-ray image sequence for complicated components. To improve the self-adaption of extraction, a method is presented in this paper. In thi...A key step is to extract valid information region in the fusion of multi-voltage X-ray image sequence for complicated components. To improve the self-adaption of extraction, a method is presented in this paper. In this paper, the valid informa-tion region is selected by the grey level interval, which is computed by the optimization of image quality evaluation model. The model is based on the histogram equalization and the grey level interval. Then, every valid region of images at different voltages is extracted and they are fused according their grey level transformation function. The fusion image contains completed struc-ture information of the component. The fusion experiment of a cylinder head shows the effectiveness of the presented method.展开更多
Field environmental sensing can acquire real-time environmental information,which will be applied to field operation,through the fusion of multiple sensors.Multi-sensor fusion refers to the fusion of information obtai...Field environmental sensing can acquire real-time environmental information,which will be applied to field operation,through the fusion of multiple sensors.Multi-sensor fusion refers to the fusion of information obtained from multiple sensors using more advanced data processing methods.The main objective of applying this technology in field environment perception is to acquire real-time environmental information,making agricultural mechanical devices operate better in complex farmland environment with stronger sensing ability and operational accuracy.In this paper,the characteristics of sensors are studied to clarify the advantages and existing problems of each type of sensors and point out that multiple sensors can be introduced to compensate for the information loss.Secondly,the mainstream information fusion types at present are outlined.The characteristics,advantages and disadvantages of different fusion methods are analyzed.The important studies and applications related to multi-sensor information fusion technology published at home and abroad are listed.Eventually,the existing problems in the field environment sensing at present are summarized and the prospect for future of sensors precise sensing,multi-dimensional fusion strategies,discrepancies in sensor fusion and agricultural information processing are proposed in hope of providing reference for the deeper development of smart agriculture.展开更多
The current life-prediction models for lithium-ion batteries have several problems, such as the construction of complex feature structures, a high number of feature dimensions, and inaccurate prediction results. To ov...The current life-prediction models for lithium-ion batteries have several problems, such as the construction of complex feature structures, a high number of feature dimensions, and inaccurate prediction results. To overcome these problems, this paper proposes a deep-learning model combining an autoencoder network and a long short-term memory network. First, this model applies the characteristics of the autoencoder to reduce the dimensionality of the high-dimensional features extracted from the battery data set and realize the fusion of complex time-domain features, which overcomes the problems of redundant model information and low computational efficiency. This model then uses a long short-term memory network that is sensitive to time-series data to solve the long-path dependence problem in the prediction of battery life. Lastly, the attention mechanism is used to give greater weight to features that have a greater impact on the target value, which enhances the learning effect of the model on the long input sequence. To verify the efficacy of the proposed model, this paper uses NASA's lithium-ion battery cycle life data set.展开更多
The treatment of pathologies in the thoracic spine is a challenge. The periodic failure of pedicle screw insertion and anatomical variations make the search for an alternative to pedicle screws in thoracic spine surge...The treatment of pathologies in the thoracic spine is a challenge. The periodic failure of pedicle screw insertion and anatomical variations make the search for an alternative to pedicle screws in thoracic spine surgery necessary. The interlaminar crossed screws is a well-known and secure method for fusion in cervical spine, and in thoracic spine there used to be insufficient clinical data to support this technique, until now. We demonstrate in an initial series of 10 cases treated with interlaminar fusion in association of other fusion techniques in the thoracic spine with good results. Objective: Intralaminar screws have been shown to be a biomechanical salvage technique in the thoracic spine, especially in long cervicothoracic, thoracic and thoracolumbar fixation. The goals of this article are to demonstrate our initial experience and the range of indications for thoracic crossed intralaminar screws. Methods: In this article we describe our initial series performed at São Teotónio Hospital in Viseu, Portugal, and our results, and also provide a comprehensive review of the recent literature in the use of intralaminar crossed fixation.展开更多
Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas,there is a deficiency of relevant research,operational...Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas,there is a deficiency of relevant research,operational techniques,and experience.This made providing meteorological services for this event particularly challenging.The China Meteorological Administration(CMA)Earth System Modeling and Prediction Centre,achieved breakthroughs in research on short-and medium-term deterministic and ensemble numerical predictions.Several key technologies crucial for precise winter weather services during the Winter Olympics were developed.A comprehensive framework,known as the Operational System for High-Precision Weather Forecasting for the Winter Olympics,was established.Some of these advancements represent the highest level of capabilities currently available in China.The meteorological service provided to the Beijing 2022 Games also exceeded previous Winter Olympic Games in both variety and quality.This included achievements such as the“100-meter level,minute level”downscaled spatiotemporal resolution and forecasts spanning 1 to 15 days.Around 30 new technologies and over 60 kinds of products that align with the requirements of the Winter Olympics Organizing Committee were developed,and many of these techniques have since been integrated into the CMA’s operational national forecasting systems.These accomplishments were facilitated by a dedicated weather forecasting and research initiative,in conjunction with the preexisting real-time operational forecasting systems of the CMA.This program represents one of the five subprograms of the WMO’s high-impact weather forecasting demonstration project(SMART2022),and continues to play an important role in their Regional Association(RA)II Research Development Project(Hangzhou RDP).Therefore,the research accomplishments and meteorological service experiences from this program will be carried forward into forthcoming highimpact weather forecasting activities.This article provides an overview and assessment of this program and the operational national forecasting systems.展开更多
Conventionally,soil cadmium(Cd)measurements in the laboratory are expensive and timeconsuming,involving complex processes of sample preparation and chemical analysis.This study aimed to identify the feasibility of usi...Conventionally,soil cadmium(Cd)measurements in the laboratory are expensive and timeconsuming,involving complex processes of sample preparation and chemical analysis.This study aimed to identify the feasibility of using sensor data of visible near-infrared reflectance(Vis-NIR)spectroscopy and portable X-ray fluorescence spectrometry(PXRF)to estimate regional soil Cd concentration in a time-and cost-savingmanner.The sensor data of Vis-NIR and PXRF,and Cd concentrations of 128 surface soils from Yunnan Province,China,were measured.Outer-product analysis(OPA)was used for synthesizing the sensor data and Granger-Ramanathan averaging(GRA)was applied to fuse the model results.Artificial neural network(ANN)models were built using Vis-NIR data,PXRF data,and OPA data,respectively.Results showed that:(1)ANN model based on PXRF data performed better than that based on Vis-NIR data for soil Cd estimation;(2)Fusion methods of both OPA and GRA had higher predictive power(R^(2))=0.89,ratios of performance to interquartile range(RPIQ)=4.14,and lower root mean squared error(RMSE)=0.06,in ANN model based on OPA fusion;R^(2)=0.88,RMSE=0.06,and RPIQ=3.53 in GRA model)than those based on either Vis-NIR data or PXRF data.In conclusion,there exists a great potential for the combination of OPA fusion and ANN to estimate soil Cd concentration rapidly and accurately.展开更多
Agricultural applications of remote sensing data typically require high spatial resolution and frequent observations.The increasing availability of high spatial resolution imagery meets the spatial resolution requirem...Agricultural applications of remote sensing data typically require high spatial resolution and frequent observations.The increasing availability of high spatial resolution imagery meets the spatial resolution requirement well.However,the long revisit period and frequent cloud contamination severely compromise their ability to monitor crop growth,which is characterized by high temporal heterogeneity.Many spatiotemporal fusion methods have been developed to produce synthetic images with high spatial and temporal resolutions.However,these existing methods focus on fusing low and medium spatial resolution satellite data in terms of model development and validation.When it comes to fusing medium and high spatial resolution images,the applicability remains unknown and may face various challenges.To address this issue,we propose a novel spatiotemporal fusion method,the dual-stream spatiotemporal decoupling fusion architecture model,to fully realize the prediction of high spatial resolution images.Compared with other fusion methods,the model has distinct advantages:(a)It maintains high fusion accuracy and good spatial detail by combining deep-learning-based super-resolution method and partial least squares regression model through edge and color-based weighting loss function;and(b)it demonstrates improved transferability over time by introducing image gradient maps and partial least squares regression model.We tested the StarFusion model at 3 experimental sites and compared it with 4 traditional methods:STARFM(spatial and temporal adaptive reflectance fusion),FSDAF(flexible spatiotemporal data fusion),Fit-FC(regression model fitting,spatial filtering,and residual compensation),FIRST(fusion incorporating spectral autocorrelation),and a deep learning base method-super-resolution generative adversarial network.In addition,we also investigated the possibility of our method to use multiple pairs of coarse and fine images in the training process.The results show that multiple pairs of images provide better overall performance but both of them are better than other comparison methods.Considering the difficulty in obtaining multiple cloud-free image pairs in practice,our method is recommended to provide high-quality Gaofen-1 data with improved temporal resolution in most cases since the performance degradation of single pair is not significant.展开更多
The glass sample based on the composition of 45PbF_2-45GeO_2-10WO_3 co-doped with Yb^(3+)/Er^(3+) was prepared by the fusion method in two steps: melted at 950 ℃ for 20～25 min then annealed at 380 ℃ for 4 h. Throug...The glass sample based on the composition of 45PbF_2-45GeO_2-10WO_3 co-doped with Yb^(3+)/Er^(3+) was prepared by the fusion method in two steps: melted at 950 ℃ for 20～25 min then annealed at 380 ℃ for 4 h. Through the V-prism it is found that the refractive index of host glass and the sample are 1.517 and 1.65 respectively. The transmittance was observed by using the ultraviolet-visible-infrared spectrometer in the wavelength range from 0.35 to 2.5μm. The transmittance of the host glass is beyond 73%. That of the sample is beyond 50% and there are characteristic absorption peaks of rare-earth ions. The emission spectrum was measured by using the Hitachi F-4500 fluorescent spectrometer pumped by 980 nm semiconductor laser. There are a strong emission peak at 530 nm and a weak peak at 650 nm.展开更多
The stability of the subsea oil and gas production system is heavily influenced by slug flow. One successful method of managing slug flow is to use top valve control based on subsea pipeline pressure. However, the com...The stability of the subsea oil and gas production system is heavily influenced by slug flow. One successful method of managing slug flow is to use top valve control based on subsea pipeline pressure. However, the complexity of production makes it difficult to measure the pressure of subsea pipelines, and measured values are not always accessible in real-time. The research introduces a technique for integrating Unscented Kalman Filter (UKF) and Wavelet Neural Network (WNN) to estimate the state of subsea pipeline pressure using historical data and a state model. The proposed method treats multiphase flow transport as a nonlinear model, with a dynamic WNN serving as the state observer. To achieve real-time state estimation, the WNN is included into the UKF algorithm to create a WNN-based UKF state equation. Integrate WNN and UKF in a novel way to predict system state accurately. The simulated results show that the approach can efficiently predict the inlet pressure and manage the slug flow in real-time using the riser's top pressure, outlet flow and valve opening. This method of estimate can significantly increase the control effect.展开更多
Content-based medical image retrieval(CBMIR)is a technique for retrieving medical images based on automatically derived image features.There are many applications of CBMIR,such as teaching,research,diagnosis and elect...Content-based medical image retrieval(CBMIR)is a technique for retrieving medical images based on automatically derived image features.There are many applications of CBMIR,such as teaching,research,diagnosis and electronic patient records.Several methods are applied to enhance the retrieval performance of CBMIR systems.Developing new and effective similarity measure and features fusion methods are two of the most powerful and effective strategies for improving these systems.This study proposes the relative difference-based similarity measure(RDBSM)for CBMIR.The new measure was first used in the similarity calculation stage for the CBMIR using an unweighted fusion method of traditional color and texture features.Furthermore,the study also proposes a weighted fusion method for medical image features extracted using pre-trained convolutional neural networks(CNNs)models.Our proposed RDBSM has outperformed the standard well-known similarity and distance measures using two popular medical image datasets,Kvasir and PH2,in terms of recall and precision retrieval measures.The effectiveness and quality of our proposed similarity measure are also proved using a significant test and statistical confidence bound.展开更多
English is one of the core subjects in compulsory education. To carry out English teaching in a scientific and reasonable way is of great significance to the cultivation of primary school students' core qualities ...English is one of the core subjects in compulsory education. To carry out English teaching in a scientific and reasonable way is of great significance to the cultivation of primary school students' core qualities such as language ability, cultural awareness and learning ability. Using English picture books to carry out reading teaching is a new trend in English teaching in recent years. There are many stories with complete context in English picture books. Using these stories to carry out English teaching can on the one hand stimulate students' interest in learning English, and on the other hand help students get more language input. In view of this, it is very necessary to promote the integration of primary school English picture books reading and main textbooks. Therefore, based on my own teaching experience, the author explores the strategy of integrating English picture books with main textbooks in order to provide theoretical basis for primary school English teachers' teaching.展开更多
The purpose of this paper is to present a general universal formula for <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;&...The purpose of this paper is to present a general universal formula for <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;">-variate survival functions for arbitrary <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> = 2, 3, <span style="font-family:;" "=""><span style="font-family:Verdana;">...<span style="font-family:Verdana;">, given all the univariate marginal survival functions. This universal form of <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;">-variate probability distributions was obtained by means of “dependence functions” named “joiners” in the text. These joiners determine all the involved stochastic dependencies between the underlying random variables. However, in order that the presented formula (the form) represents a legitimate survival function, some necessary and sufficient conditions for the joiners had to be found. Basically, finding those conditions is the main task of this paper. This task was successfully performed for the case <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;"> = 2 and the main results for the case <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;"> = 3 were formulated as Theorem 1 and Theorem 2 in Section 4. Nevertheless, the hypothetical conditions valid for the general <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;"> ≥ 4 case were also formulated in Section 3 as the (very convincing) Hypothesis. As for the sufficient conditions for both the <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:;" "=""><span style="font-family:Verdana;"> = 3 and <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;"> ≥ 4 cases, the full generality was not achieved since two restrictions were imposed. Firstly, we limited ourselves to the, defined in the text, “continuous cases” (when the corresponding joint density exists and is continuous), and secondly we consider positive stochastic dependencies only. Nevertheless, the class of the <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;">-variate distributions which can be constructed is very wide. The presented method of construction by means of joiners can be considered competitive to the <span style="font-family:Verdana;"><span style="font-family:Verdana;">copula<span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> methodology. As it is suggested in the paper the possibility of building a common theory of both copulae and joiners is quite possible, and the joiners may play the role of tools within the theory of copulae, and vice versa copulae may, for example, be used for finding proper joiners. Another independent feature of the joiners methodology is the possibility of constructing many new stochastic processes including stationary and Markovian.展开更多
基金funded by the Committee of Science of the Ministry of Science andHigher Education of the Republic of Kazakhstan(Grant No.BR24993166).
文摘While automatic image captioning systems have made notable progress in the past few years,generating captions that fully convey sentiment remains a considerable challenge.Although existing models achieve strong performance in visual recognition and factual description,they often fail to account for the emotional context that is naturally present in human-generated captions.To address this gap,we propose the Sentiment-Driven Caption Generator(SDCG),which combines transformer-based visual and textual processing withmulti-level fusion.RoBERTa is used for extracting sentiment from textual input,while visual features are handled by the Vision Transformer(ViT).These features are fused using several fusion approaches,including Concatenation,Attention,Visual-Sentiment Co-Attention(VSCA),and Cross-Attention.Our experiments demonstrate that SDCG significantly outperforms baseline models such as the Generalized Image Transformer(GIT),which achieves 82.01%,and Bootstrapping Language-Image Pre-training(BLIP),which achieves 83.07%,in sentiment accuracy.While SDCG achieves 94.52%sentiment accuracy and improves scores in BLEU and ROUGE-L,the model demonstrates clear advantages.More importantly,the captions aremore natural,as they incorporate emotional cues and contextual awareness,making them resemble those written by a human.
基金Supported by the National Key R&D Program of China (No.2023YFC3008100)the National Natural Science Foundation of China (No.U23A2033)
文摘Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(FIR)”method for multi-sourced depth data fusion,and used it to merge the electronic nautical chart dataset(referred to as Chart2014 in this paper)with the global digital elevation dataset(referred to as Globalbath2002 in this paper).Compared to the traditional fusion of two datasets by direct combination and interpolation,the new Grid-DEM formed by FIR can better represent the data characteristics of Chart2014,reduce the calculation difficulty,and be more intuitive,and,the choice of different interpolation methods in FIR and the influence of the“exclusion radius R”parameter were discussed.FIR avoids complex calculations of spatial distances among points from different sources,and instead uses spatial exclusion map to perform one-step screening based on the exclusion radius R,which greatly improved the fusion status of a reliable dataset.The fusion results of different experiments were analyzed statistically with root mean square error and mean relative error,showing that the interpolation methods based on Delaunay triangulation are more suitable for the fusion of nautical chart depth of China,and factors such as the point density distribution of multiple source data,accuracy,interpolation method,and various terrain conditions should be fully considered when selecting the exclusion radius R.
基金Supported by National Key R&D Program of China(Grant Nos.2020YFB1709901,2020YFB1709904)National Natural Science Foundation of China(Grant Nos.51975495,51905460)+1 种基金Guangdong Provincial Basic and Applied Basic Research Foundation of China(Grant No.2021-A1515012286)Science and Technology Plan Project of Fuzhou City of China(Grant No.2022-P-022).
文摘The accurate estimation of parameters is the premise for establishing a high-fidelity simulation model of a valve-controlled cylinder system.Bench test data are easily obtained,but it is challenging to emulate actual loads in the research on parameter estimation of valve-controlled cylinder system.Despite the actual load information contained in the operating data of the control valve,its acquisition remains challenging.This paper proposes a method that fuses bench test and operating data for parameter estimation to address the aforementioned problems.The proposed method is based on Bayesian theory,and its core is a pool fusion of prior information from bench test and operating data.Firstly,a system model is established,and the parameters in the model are analysed.Secondly,the bench and operating data of the system are collected.Then,the model parameters and weight coefficients are estimated using the data fusion method.Finally,the estimated effects of the data fusion method,Bayesian method,and particle swarm optimisation(PSO)algorithm on system model parameters are compared.The research shows that the weight coefficient represents the contribution of different prior information to the parameter estimation result.The effect of parameter estimation based on the data fusion method is better than that of the Bayesian method and the PSO algorithm.Increasing load complexity leads to a decrease in model accuracy,highlighting the crucial role of the data fusion method in parameter estimation studies.
基金funded by National Natural Science Foundation of China(Grant Nos.42272333,42277147).
文摘Refined 3D modeling of mine slopes is pivotal for precise prediction of geological hazards.Aiming at the inadequacy of existing single modeling methods in comprehensively representing the overall and localized characteristics of mining slopes,this study introduces a new method that fuses model data from Unmanned aerial vehicles(UAV)tilt photogrammetry and 3D laser scanning through a data alignment algorithm based on control points.First,the mini batch K-Medoids algorithm is utilized to cluster the point cloud data from ground 3D laser scanning.Then,the elbow rule is applied to determine the optimal cluster number(K0),and the feature points are extracted.Next,the nearest neighbor point algorithm is employed to match the feature points obtained from UAV tilt photogrammetry,and the internal point coordinates are adjusted through the distanceweighted average to construct a 3D model.Finally,by integrating an engineering case study,the K0 value is determined to be 8,with a matching accuracy between the two model datasets ranging from 0.0669 to 1.0373 mm.Therefore,compared with the modeling method utilizing K-medoids clustering algorithm,the new modeling method significantly enhances the computational efficiency,the accuracy of selecting the optimal number of feature points in 3D laser scanning,and the precision of the 3D model derived from UAV tilt photogrammetry.This method provides a research foundation for constructing mine slope model.
基金the National Natural Science Foundation of China(No.61975015)the Research and Innovation Project for Graduate Students at Zhongyuan University of Technology(No.YKY2024ZK14).
文摘Human posture estimation is a prominent research topic in the fields of human-com-puter interaction,motion recognition,and other intelligent applications.However,achieving highaccuracy in key point localization,which is crucial for intelligent applications,contradicts the lowdetection accuracy of human posture detection models in practical scenarios.To address this issue,a human pose estimation network called AT-HRNet has been proposed,which combines convolu-tional self-attention and cross-dimensional feature transformation.AT-HRNet captures significantfeature information from various regions in an adaptive manner,aggregating them through convolu-tional operations within the local receptive domain.The residual structures TripNeck and Trip-Block of the high-resolution network are designed to further refine the key point locations,wherethe attention weight is adjusted by a cross-dimensional interaction to obtain more features.To vali-date the effectiveness of this network,AT-HRNet was evaluated using the COCO2017 dataset.Theresults show that AT-HRNet outperforms HRNet by improving 3.2%in mAP,4.0%in AP75,and3.9%in AP^(M).This suggests that AT-HRNet can offer more beneficial solutions for human posture estimation.
基金Supported by the National Natural Science Foundation of China(No.72074201).
文摘The development of network and information technology has brought changes to the production environment of scientific and technological information,leading to the integration of multi-type scien-tific and technological information,which has become one of the primary research focuses in the cur-rent field of scientific and technological information analysis.This article proposes a basic mode to realize the fusion of multi-type scientific and technological information,expounds the corresponding basic construction method,and applies it to the scientific and technological topics identification in the field of artificial intelligence(AI).The research results show that the multi-type scientific and technological information fusion mode proposed in this article has certain feasibility in specific appli-cation scenarios,which lays a foundation for the subsequent research work.
基金supported by the National Natural Science Foundation of China (No. 52075350)the Special City School Strategic Cooperation Project of Sichuan University and Zigong (No.2021CDZG-3)
文摘The control rod drive mechanism(CRDM)is an essential part of the control and safety protection system of pressurized water reactors.Current CRDM simulations are mostly performed collectively using a single method,ignoring the influence of multiple motion units and the differences in various features among them,which strongly affect the efficiency and accuracy of the simulations.In this study,we constructed a flow field fusion simulation method based on model features by combining key motion unit analysis and various simulation methods and then applied the method to the CRDM simulation process.CRDM performs motion unit decomposition through the structural hierarchy of function-movement-action method,and the key meta-actions are identified as the nodes in the flow field simulation.We established a fused feature-based multimethod simulation process and processed the simulation methods and data according to the features of the fluid domain space and the structural complexity to obtain the fusion simulation results.Compared to traditional simulation methods and real measurements,the simulation method provides advantages in terms of simulation efficiency and accuracy.
文摘Weighted fusion algorithms, which can be applied in the area of multi-sensor data fusion, are advanced based on weighted least square method. A weighted fusion algorithm, in which the relationship between weight coefficients and measurement noise is established, is proposed by giving attention to the correlation of measurement noise. Then a simplified weighted fusion algorithm is deduced on the assumption that measurement noise is uncorrelated. In addition, an algorithm, which can adjust the weight coefficients in the simplified algorithm by making estimations of measurement noise from measurements, is presented. It is proved by emulation and experiment that the precision performance of the multi-sensor system based on these algorithms is better than that of the multi-sensor system based on other algorithms.
基金National Natural Science Foundation of China(No.61227003,No.61301259,No.61471325and No.61571404)Natural Science Foundation of Shanxi Province(No.2015021099)
文摘A key step is to extract valid information region in the fusion of multi-voltage X-ray image sequence for complicated components. To improve the self-adaption of extraction, a method is presented in this paper. In this paper, the valid informa-tion region is selected by the grey level interval, which is computed by the optimization of image quality evaluation model. The model is based on the histogram equalization and the grey level interval. Then, every valid region of images at different voltages is extracted and they are fused according their grey level transformation function. The fusion image contains completed struc-ture information of the component. The fusion experiment of a cylinder head shows the effectiveness of the presented method.
基金supported by the National Natural Science Foundation of China(Grant No.52272438)the Jiangsu Agricultural Science and Technology Innovation[Grant No.CX(21)3149]+1 种基金the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences(Grant No.Yueshengjihua-2206)the Jiangsu Province and Education Ministry Co-sponsored Synergistic Innovation Center of Modern Agricultural Equipment(Grant No.XTCX2007).
文摘Field environmental sensing can acquire real-time environmental information,which will be applied to field operation,through the fusion of multiple sensors.Multi-sensor fusion refers to the fusion of information obtained from multiple sensors using more advanced data processing methods.The main objective of applying this technology in field environment perception is to acquire real-time environmental information,making agricultural mechanical devices operate better in complex farmland environment with stronger sensing ability and operational accuracy.In this paper,the characteristics of sensors are studied to clarify the advantages and existing problems of each type of sensors and point out that multiple sensors can be introduced to compensate for the information loss.Secondly,the mainstream information fusion types at present are outlined.The characteristics,advantages and disadvantages of different fusion methods are analyzed.The important studies and applications related to multi-sensor information fusion technology published at home and abroad are listed.Eventually,the existing problems in the field environment sensing at present are summarized and the prospect for future of sensors precise sensing,multi-dimensional fusion strategies,discrepancies in sensor fusion and agricultural information processing are proposed in hope of providing reference for the deeper development of smart agriculture.
基金supported by the National Natural Science Foundation of China (No.61871350)the Zhejiang Science and Technology Plan Project (No.2019C011123)the Zhejiang Province Basic Public Welfare Research Project (No.LGG19F030011)。
文摘The current life-prediction models for lithium-ion batteries have several problems, such as the construction of complex feature structures, a high number of feature dimensions, and inaccurate prediction results. To overcome these problems, this paper proposes a deep-learning model combining an autoencoder network and a long short-term memory network. First, this model applies the characteristics of the autoencoder to reduce the dimensionality of the high-dimensional features extracted from the battery data set and realize the fusion of complex time-domain features, which overcomes the problems of redundant model information and low computational efficiency. This model then uses a long short-term memory network that is sensitive to time-series data to solve the long-path dependence problem in the prediction of battery life. Lastly, the attention mechanism is used to give greater weight to features that have a greater impact on the target value, which enhances the learning effect of the model on the long input sequence. To verify the efficacy of the proposed model, this paper uses NASA's lithium-ion battery cycle life data set.
文摘The treatment of pathologies in the thoracic spine is a challenge. The periodic failure of pedicle screw insertion and anatomical variations make the search for an alternative to pedicle screws in thoracic spine surgery necessary. The interlaminar crossed screws is a well-known and secure method for fusion in cervical spine, and in thoracic spine there used to be insufficient clinical data to support this technique, until now. We demonstrate in an initial series of 10 cases treated with interlaminar fusion in association of other fusion techniques in the thoracic spine with good results. Objective: Intralaminar screws have been shown to be a biomechanical salvage technique in the thoracic spine, especially in long cervicothoracic, thoracic and thoracolumbar fixation. The goals of this article are to demonstrate our initial experience and the range of indications for thoracic crossed intralaminar screws. Methods: In this article we describe our initial series performed at São Teotónio Hospital in Viseu, Portugal, and our results, and also provide a comprehensive review of the recent literature in the use of intralaminar crossed fixation.
基金This work was jointly supported by the National Natural Science Foundation of China(Grant Nos.41975137,42175012,and 41475097)the National Key Research and Development Program(Grant No.2018YFF0300103).
文摘Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas,there is a deficiency of relevant research,operational techniques,and experience.This made providing meteorological services for this event particularly challenging.The China Meteorological Administration(CMA)Earth System Modeling and Prediction Centre,achieved breakthroughs in research on short-and medium-term deterministic and ensemble numerical predictions.Several key technologies crucial for precise winter weather services during the Winter Olympics were developed.A comprehensive framework,known as the Operational System for High-Precision Weather Forecasting for the Winter Olympics,was established.Some of these advancements represent the highest level of capabilities currently available in China.The meteorological service provided to the Beijing 2022 Games also exceeded previous Winter Olympic Games in both variety and quality.This included achievements such as the“100-meter level,minute level”downscaled spatiotemporal resolution and forecasts spanning 1 to 15 days.Around 30 new technologies and over 60 kinds of products that align with the requirements of the Winter Olympics Organizing Committee were developed,and many of these techniques have since been integrated into the CMA’s operational national forecasting systems.These accomplishments were facilitated by a dedicated weather forecasting and research initiative,in conjunction with the preexisting real-time operational forecasting systems of the CMA.This program represents one of the five subprograms of the WMO’s high-impact weather forecasting demonstration project(SMART2022),and continues to play an important role in their Regional Association(RA)II Research Development Project(Hangzhou RDP).Therefore,the research accomplishments and meteorological service experiences from this program will be carried forward into forthcoming highimpact weather forecasting activities.This article provides an overview and assessment of this program and the operational national forecasting systems.
基金supported by the National Key Research and Development Project(No.2020YFC1807405)the China Postdoctoral Science Foundation(No.2021M703301)+1 种基金the Key-Area Research and Development Program of Guangdong Province(No.2020B0202010006)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(No.2019312).
文摘Conventionally,soil cadmium(Cd)measurements in the laboratory are expensive and timeconsuming,involving complex processes of sample preparation and chemical analysis.This study aimed to identify the feasibility of using sensor data of visible near-infrared reflectance(Vis-NIR)spectroscopy and portable X-ray fluorescence spectrometry(PXRF)to estimate regional soil Cd concentration in a time-and cost-savingmanner.The sensor data of Vis-NIR and PXRF,and Cd concentrations of 128 surface soils from Yunnan Province,China,were measured.Outer-product analysis(OPA)was used for synthesizing the sensor data and Granger-Ramanathan averaging(GRA)was applied to fuse the model results.Artificial neural network(ANN)models were built using Vis-NIR data,PXRF data,and OPA data,respectively.Results showed that:(1)ANN model based on PXRF data performed better than that based on Vis-NIR data for soil Cd estimation;(2)Fusion methods of both OPA and GRA had higher predictive power(R^(2))=0.89,ratios of performance to interquartile range(RPIQ)=4.14,and lower root mean squared error(RMSE)=0.06,in ANN model based on OPA fusion;R^(2)=0.88,RMSE=0.06,and RPIQ=3.53 in GRA model)than those based on either Vis-NIR data or PXRF data.In conclusion,there exists a great potential for the combination of OPA fusion and ANN to estimate soil Cd concentration rapidly and accurately.
基金supported by High-Resolution Earth Observation System(09-Y30F01-9001-20/22).
文摘Agricultural applications of remote sensing data typically require high spatial resolution and frequent observations.The increasing availability of high spatial resolution imagery meets the spatial resolution requirement well.However,the long revisit period and frequent cloud contamination severely compromise their ability to monitor crop growth,which is characterized by high temporal heterogeneity.Many spatiotemporal fusion methods have been developed to produce synthetic images with high spatial and temporal resolutions.However,these existing methods focus on fusing low and medium spatial resolution satellite data in terms of model development and validation.When it comes to fusing medium and high spatial resolution images,the applicability remains unknown and may face various challenges.To address this issue,we propose a novel spatiotemporal fusion method,the dual-stream spatiotemporal decoupling fusion architecture model,to fully realize the prediction of high spatial resolution images.Compared with other fusion methods,the model has distinct advantages:(a)It maintains high fusion accuracy and good spatial detail by combining deep-learning-based super-resolution method and partial least squares regression model through edge and color-based weighting loss function;and(b)it demonstrates improved transferability over time by introducing image gradient maps and partial least squares regression model.We tested the StarFusion model at 3 experimental sites and compared it with 4 traditional methods:STARFM(spatial and temporal adaptive reflectance fusion),FSDAF(flexible spatiotemporal data fusion),Fit-FC(regression model fitting,spatial filtering,and residual compensation),FIRST(fusion incorporating spectral autocorrelation),and a deep learning base method-super-resolution generative adversarial network.In addition,we also investigated the possibility of our method to use multiple pairs of coarse and fine images in the training process.The results show that multiple pairs of images provide better overall performance but both of them are better than other comparison methods.Considering the difficulty in obtaining multiple cloud-free image pairs in practice,our method is recommended to provide high-quality Gaofen-1 data with improved temporal resolution in most cases since the performance degradation of single pair is not significant.
文摘The glass sample based on the composition of 45PbF_2-45GeO_2-10WO_3 co-doped with Yb^(3+)/Er^(3+) was prepared by the fusion method in two steps: melted at 950 ℃ for 20～25 min then annealed at 380 ℃ for 4 h. Through the V-prism it is found that the refractive index of host glass and the sample are 1.517 and 1.65 respectively. The transmittance was observed by using the ultraviolet-visible-infrared spectrometer in the wavelength range from 0.35 to 2.5μm. The transmittance of the host glass is beyond 73%. That of the sample is beyond 50% and there are characteristic absorption peaks of rare-earth ions. The emission spectrum was measured by using the Hitachi F-4500 fluorescent spectrometer pumped by 980 nm semiconductor laser. There are a strong emission peak at 530 nm and a weak peak at 650 nm.
基金supported by Development Project in Key Technical Field of Sichuan Province(2019ZDZX0030)International Science and Technology Innovation Cooperation Program of Sichuan Province(2021YFH0115)+1 种基金Nanchong-SWPU Science and Technology Strategic Cooperation Project(SXHZ057)Key and Core Technology Breakthrough Project of CNPC(2021ZG08).
文摘The stability of the subsea oil and gas production system is heavily influenced by slug flow. One successful method of managing slug flow is to use top valve control based on subsea pipeline pressure. However, the complexity of production makes it difficult to measure the pressure of subsea pipelines, and measured values are not always accessible in real-time. The research introduces a technique for integrating Unscented Kalman Filter (UKF) and Wavelet Neural Network (WNN) to estimate the state of subsea pipeline pressure using historical data and a state model. The proposed method treats multiphase flow transport as a nonlinear model, with a dynamic WNN serving as the state observer. To achieve real-time state estimation, the WNN is included into the UKF algorithm to create a WNN-based UKF state equation. Integrate WNN and UKF in a novel way to predict system state accurately. The simulated results show that the approach can efficiently predict the inlet pressure and manage the slug flow in real-time using the riser's top pressure, outlet flow and valve opening. This method of estimate can significantly increase the control effect.
基金funded by the Deanship of Scientific Research (DSR)at King Abdulaziz University,Jeddah,Saudi Arabia,Under Grant No. (G:146-830-1441).
文摘Content-based medical image retrieval(CBMIR)is a technique for retrieving medical images based on automatically derived image features.There are many applications of CBMIR,such as teaching,research,diagnosis and electronic patient records.Several methods are applied to enhance the retrieval performance of CBMIR systems.Developing new and effective similarity measure and features fusion methods are two of the most powerful and effective strategies for improving these systems.This study proposes the relative difference-based similarity measure(RDBSM)for CBMIR.The new measure was first used in the similarity calculation stage for the CBMIR using an unweighted fusion method of traditional color and texture features.Furthermore,the study also proposes a weighted fusion method for medical image features extracted using pre-trained convolutional neural networks(CNNs)models.Our proposed RDBSM has outperformed the standard well-known similarity and distance measures using two popular medical image datasets,Kvasir and PH2,in terms of recall and precision retrieval measures.The effectiveness and quality of our proposed similarity measure are also proved using a significant test and statistical confidence bound.
文摘English is one of the core subjects in compulsory education. To carry out English teaching in a scientific and reasonable way is of great significance to the cultivation of primary school students' core qualities such as language ability, cultural awareness and learning ability. Using English picture books to carry out reading teaching is a new trend in English teaching in recent years. There are many stories with complete context in English picture books. Using these stories to carry out English teaching can on the one hand stimulate students' interest in learning English, and on the other hand help students get more language input. In view of this, it is very necessary to promote the integration of primary school English picture books reading and main textbooks. Therefore, based on my own teaching experience, the author explores the strategy of integrating English picture books with main textbooks in order to provide theoretical basis for primary school English teachers' teaching.
文摘The purpose of this paper is to present a general universal formula for <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;">-variate survival functions for arbitrary <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> = 2, 3, <span style="font-family:;" "=""><span style="font-family:Verdana;">...<span style="font-family:Verdana;">, given all the univariate marginal survival functions. This universal form of <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;">-variate probability distributions was obtained by means of “dependence functions” named “joiners” in the text. These joiners determine all the involved stochastic dependencies between the underlying random variables. However, in order that the presented formula (the form) represents a legitimate survival function, some necessary and sufficient conditions for the joiners had to be found. Basically, finding those conditions is the main task of this paper. This task was successfully performed for the case <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;"> = 2 and the main results for the case <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;"> = 3 were formulated as Theorem 1 and Theorem 2 in Section 4. Nevertheless, the hypothetical conditions valid for the general <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;"> ≥ 4 case were also formulated in Section 3 as the (very convincing) Hypothesis. As for the sufficient conditions for both the <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:;" "=""><span style="font-family:Verdana;"> = 3 and <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;"> ≥ 4 cases, the full generality was not achieved since two restrictions were imposed. Firstly, we limited ourselves to the, defined in the text, “continuous cases” (when the corresponding joint density exists and is continuous), and secondly we consider positive stochastic dependencies only. Nevertheless, the class of the <span style="font-family:Verdana;"><span style="font-family:Verdana;">k<span style="font-family:Verdana;"><span style="font-family:Verdana;">-variate distributions which can be constructed is very wide. The presented method of construction by means of joiners can be considered competitive to the <span style="font-family:Verdana;"><span style="font-family:Verdana;">copula<span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> methodology. As it is suggested in the paper the possibility of building a common theory of both copulae and joiners is quite possible, and the joiners may play the role of tools within the theory of copulae, and vice versa copulae may, for example, be used for finding proper joiners. Another independent feature of the joiners methodology is the possibility of constructing many new stochastic processes including stationary and Markovian.
