This article broadens terminology and approaches that continue to advance time modelling within a relationalist framework. Time is modeled as a single dimension, flowing continuously through independent privileged poi...This article broadens terminology and approaches that continue to advance time modelling within a relationalist framework. Time is modeled as a single dimension, flowing continuously through independent privileged points. Introduced as absolute point-time, abstract continuous time is a backdrop for concrete relational-based time that is finite and discrete, bound to the limits of a real-world system. We discuss how discrete signals at a point are used to temporally anchor zero-temporal points [t = 0] in linear time. Object-oriented temporal line elements, flanked by temporal point elements, have a proportional geometric identity quantifiable by a standard unit system and can be mapped on a natural number line. Durations, line elements, are divisible into ordered unit ratio elements using ancient timekeeping formulas. The divisional structure provides temporal classes for rotational (Rt24t) and orbital (Rt18) sample periods, as well as a more general temporal class (Rt12) applicable to either sample or frame periods. We introduce notation for additive cyclic counts of sample periods, including divisional units, for calendar-like formatting. For system modeling, unit structures with dihedral symmetry, group order, and numerical order are shown to be applicable to Euclidean modelling. We introduce new functions for bijective and non-bijective mapping, modular arithmetic for cyclic-based time counts, and a novel formula relating to a subgroup of Pythagorean triples, preserving dihedral n-polygon symmetries. This article presents a new approach to model time in a relationalistic framework.展开更多
The present technical paper outlines the details of the controlled blasting techniques used to optimize blasting pattern for excavation of hard rock near the Bhira Earthen Dam in Maharashtra,India.In this connection,a...The present technical paper outlines the details of the controlled blasting techniques used to optimize blasting pattern for excavation of hard rock near the Bhira Earthen Dam in Maharashtra,India.In this connection,a series of experimental blasts were conducted by adjusting various blast design parameters at project site.The safe charge weight per delay was kept between 0.125 and 0.375 kg.The outcomes of these experimental blasts were analyzed to recommend optimized blasting patterns and methods for the overall excavation process during actual blasting operations.Blast design parameters,including the maximum quantity of explosive per delay,hole depth,burden and spacing between holes were optimized by using a site-specific attenuation equation,taking into account the proximity of the dam and tunnel from the blasting area.Peak particle velocity(PPV)level of 10 mm/s and 50 mm/s respectively were adopted as the safe vibration level for ensuring safety of the Bhira Earthen Dam and the nearby tunnel from the adverse effects of blast vibrations by analyzing the dominant frequency of ground vibrations observed and also by reviewing various international standards.Frequency of the ground vibrations observed on the dam and tunnel from majority of the blasts was found to be more than 10 Hz and 50 Hz respectively.During the entire period of blasting,the blast vibrations were recorded to be far lower than the safe vibration level set for these structures.Maximum Vibration level of about 0.8 mm/s and 35 mm/s were observed on dam and tunnel respectively which are far lower than the safe vibration level adopted for these structures.Hence,the entire excavation work was completed successfully and safely,without endangering the safety of dam or tunnel.展开更多
The concept of matching energy was proposed by Gutman and Wagner firstly in 2012. Let G be a simple graph of order n and λ1, λ2, . . . , λn be the zeros of its matching polynomial. The matching energy of a graph G ...The concept of matching energy was proposed by Gutman and Wagner firstly in 2012. Let G be a simple graph of order n and λ1, λ2, . . . , λn be the zeros of its matching polynomial. The matching energy of a graph G is defined as ME(G) = Pni=1 |λi|. By the famous Coulson’s formula, matching energies can also be calculated by an improper integral depending on a parameter. A k-claw attaching graph Gu(k) refers to the graph obtained by attaching k pendent edges to the graph G at the vertex u, where u is called the root of Gu(k). In this paper, we use some theories of mathematical analysis to obtain a new technique to compare the matching energies of two k-claw attaching graphs Gu(k) and Hv(k) with the same order, that is, limk→∞[ME(Gu(k)) − ME(Hv(k))] = ME(G − u) − ME(H − v). By the technique, we finally determine unicyclic graphs of order n with the 9th to 13th minimal matching energies for all n ≥ 58.展开更多
In recent years,with the rapid development of deep learning technology,relational triplet extraction techniques have also achieved groundbreaking progress.Traditional pipeline models have certain limitations due to er...In recent years,with the rapid development of deep learning technology,relational triplet extraction techniques have also achieved groundbreaking progress.Traditional pipeline models have certain limitations due to error propagation.To overcome the limitations of traditional pipeline models,recent research has focused on jointly modeling the two key subtasks-named entity recognition and relation extraction-within a unified framework.To support future research,this paper provides a comprehensive review of recently published studies in the field of relational triplet extraction.The review examines commonly used public datasets for relational triplet extraction techniques and systematically reviews current mainstream joint extraction methods,including joint decoding methods and parameter sharing methods,with joint decoding methods further divided into table filling,tagging,and sequence-to-sequence approaches.In addition,this paper also conducts small-scale replication experiments on models that have performed well in recent years for each method to verify the reproducibility of the code and to compare the performance of different models under uniform conditions.Each method has its own advantages in terms of model design,task handling,and application scenarios,but also faces challenges such as processing complex sentence structures,cross-sentence relation extraction,and adaptability in low-resource environments.Finally,this paper systematically summarizes each method and discusses the future development prospects of joint extraction of relational triples.展开更多
The aim of the study is to explore the essential characteristic of tourism,transport,and terrorism and to highlight the connection between them.Tourism as a phenomenon is related to the question“why do people travel?...The aim of the study is to explore the essential characteristic of tourism,transport,and terrorism and to highlight the connection between them.Tourism as a phenomenon is related to the question“why do people travel?”.The answer to this question requires clarifying a number of sociological and psychological features such as leisure and budget time travel,motivation for travel,psychological benefits,fashion,terrorism,and more.Tourism is a socio-economic and cultural phenomenon that has multiple manifestations.It is one of the factors and driving forces of globalization.Its operation and development leads to the emergence of different economic,socio-cultural,environmental,political,and health effects,making it an indispensable part of modern life.展开更多
Dispersion characteristics of magnonic crystals have attracted considerable attention because of the potential applications for spin-wave devices.In this work,we investigated the strain-manipulated dispersion characte...Dispersion characteristics of magnonic crystals have attracted considerable attention because of the potential applications for spin-wave devices.In this work,we investigated the strain-manipulated dispersion characteristics of magnonic crystals with Dzyaloshinskii–Moriya interaction(DMI)and discussed the potential applications in spin-wave devices.Here,the ground states and stabilities of the magnonic crystals were investigated.Then,the strain-manipulated dispersion characteristics of the magnonic crystals based on domains and skyrmions were studied.The simulation results indicated that,the applied strain could manipulate the band widths and the positions of the allowed frequency bands.Finally,the realization of magnonic crystal heterojunctions and potential applications in spin-wave devices,such as filters,diodes,and transistors based on strain-manipulated magnonic crystals were proposed.Our research provides a theoretical foundation for designing tunable spin-wave devices based on strain-manipulated magnonic crystals with DMI.展开更多
Metastable β titanium alloy is an ideal material for lightweight and high strength due to its excellent comprehensive mechanical properties.However,overcoming the trade-off relation between strength and ductility rem...Metastable β titanium alloy is an ideal material for lightweight and high strength due to its excellent comprehensive mechanical properties.However,overcoming the trade-off relation between strength and ductility remains a significant challenge.In this study,the mechanical properties of Ti-38644 alloy were optimized by introducing a heterogeneous bi-grain bi-lamella(BG-BL)structure through a well-designed combination of rolling,drawing and heat treatment.The results demonstrate that the present BG-BL Ti-38644 alloy shows a tensile strength of~1500 MPa and a total elongation of 18%.In particular,the high strength-elongation combination of the BG-BL Ti-38644 alloy breakthroughs the trade-off relation in all the titanium alloys available.The recrystallized grains with low dislocation enhance the ductility of the Ti-38644 alloy,while the highly distorted elongated grains mainly contribute to the high strength.The present study provides a new principle for designing Ti alloys with superior strength and ductility.展开更多
On April 3,2024,a magnitude Mw 7.4 earthquake struck the city of Hualien,Taiwan,China,causing casualties and immense damage.This earthquake triggered a tsunami,which was recorded by the nearby tide gauges and Deep-Oce...On April 3,2024,a magnitude Mw 7.4 earthquake struck the city of Hualien,Taiwan,China,causing casualties and immense damage.This earthquake triggered a tsunami,which was recorded by the nearby tide gauges and Deep-Ocean Assessment and Reporting of Tsunamis(DART)buoys.These recordings are valuable for evaluating the tsunami source and quantifying the tsunami characteristics.In this study,we conduct tsunami simulations based on three earthquake source models,and analyze their reliability by comparing the computed results with observed waveforms.The evaluated source models are the United States Geological Survey(USGS)finite-fault model,and two uniform slip models using different scaling relations.The tsunami waves generated by each source are simulated with a nonhydrostatic tsunami model,which accounts for the effects of wave dispersion.The computed tsunami arrival times and wave heights are compared to the observed data and show high consistency,indicating that the magnitude and location of the earthquake source are well estimated.Also,the three source models with different rupture area and average slip lead to almost the same tsunami waves at each station,which suggests that earthquake rupture details have limited impact on far-filed tsunami records.It is also found that wave dispersion effects in this event are negligible at most stations.The findings are useful for tsunami warning.For fast warning purposes,it is practically useful to adopt simplified uniform slip models,which are able to predict the tsunami arrival time and wave height relatively well without knowing the earthquake source details.展开更多
While early transition metal-based materials,such as MXene,has emerged as an efficient catalyst for the Mg-based hydrogen storage materials,their strong interaction with hydrogen resulted in the high hydrogen diffusio...While early transition metal-based materials,such as MXene,has emerged as an efficient catalyst for the Mg-based hydrogen storage materials,their strong interaction with hydrogen resulted in the high hydrogen diffusion barrier,hindering further improvement of catalytic activity.A MXene is characterized by rich anionic groups on its surface,significantly affecting electronic and catalytic functionalities.Using Nb_(2)CT_(x)as an example,we herein illustrate the critical role of anionic T_(x)defects on controlling hydrogen dissociation and diffusion processes in Mg-based hydrogen storage materials.The hydrogen desorption properties of MgH_(2)can be significantly enhanced by utilizing T_(x)controllable Nb_(2)CT_(x),and it can release 3.57 wt.%hydrogen within 10 min under 240℃with the reduced dehydrogenation activation barrier.It also realized stable de/hydrogenation reactions for at least 50 cycles.DFT studies combined with kinetic analysis revealed that the catalyst‒hydrogen interaction could be systematically controlled by optimizing surface T_(x)defect density,accelerating the hydrogen dissociation and diffusion processes at the same time.These results demonstrate that the T_(x)defects serve as the effective catalytically active centers of Nb_(2)CT_(x),offering a flexible catalyst design guideline.展开更多
Entity relation extraction,a fundamental and essential task in natural language processing(NLP),has garnered significant attention over an extended period.,aiming to extract the core of semantic knowledge from unstruc...Entity relation extraction,a fundamental and essential task in natural language processing(NLP),has garnered significant attention over an extended period.,aiming to extract the core of semantic knowledge from unstructured text,i.e.,entities and the relations between them.At present,the main dilemma of Chinese entity relation extraction research lies in nested entities,relation overlap,and lack of entity relation interaction.This dilemma is particularly prominent in complex knowledge extraction tasks with high-density knowledge,imprecise syntactic structure,and lack of semantic roles.To address these challenges,this paper presents an innovative“character-level”Chinese part-of-speech(CN-POS)tagging approach and incorporates part-of-speech(POS)information into the pre-trained model,aiming to improve its semantic understanding and syntactic information processing capabilities.Additionally,A relation reference filling mechanism(RF)is proposed to enhance the semantic interaction between relations and entities,utilize relations to guide entity modeling,improve the boundary prediction ability of entity models for nested entity phenomena,and increase the cascading accuracy of entity-relation triples.Meanwhile,the“Queue”sub-task connection strategy is adopted to alleviate triplet cascading errors caused by overlapping relations,and a Syntax-enhanced entity relation extraction model(SE-RE)is constructed.The model showed excellent performance on the self-constructed E-commerce Product Information dataset(EPI)in this article.The results demonstrate that integrating POS enhancement into the pre-trained encoding model significantly boosts the performance of entity relation extraction models compared to baseline methods.Specifically,the F1-score fluctuation in subtasks caused by error accumulation was reduced by 3.21%,while the F1-score for entity-relation triplet extraction improved by 1.91%.展开更多
Understanding the relationship between sediment and discharge is crucial for effective river management and water-sediment modeling,especially in the Brahmaputra River,one of the large transboundary rivers with high s...Understanding the relationship between sediment and discharge is crucial for effective river management and water-sediment modeling,especially in the Brahmaputra River,one of the large transboundary rivers with high sediment and discharge variability in South Asia.Current knowledge of sediment-water relations is constrained by limited data,hindering effective transboundary river management.Using multivariate linear regression,climate elasticity coefficient,and traditional sediment rating curve,this study is designed to compare the sediment-water relations of the upstream(Nuxia)and the downstream(Bahadurabad).The results reveal significant variability between the two stations.In the upstream Nuxia,the simulation strongly correlates with observed suspended sediment load(SSL)and discharge(Q)(Pearson's r of 0.62 and 0.68,respectively).Conversely,at downstream Bahadurabad,weaker correlations(r=0.31 for sediment and r=0.51 for discharge simulation)indicate a reduced relation.This contrast reflects the non-linear nature of sediment-discharge coupling along the river continuum,shaped by both climatic and anthropogenic influences.Elasticity(ε)analysis highlights the dominant role of precipitation in shaping sediment-water dynamics(εP-SSL=2.53,εP-Q=1.01)at Nuxia,while Bahadurabad(εP-SSL=0.41,εP-Q=0.82)reflects a reduced sensitivity,possibly due to sediment retention along the floodplain.Air temperature elasticity(εT-SSL,-0.15&-3.06 at Nuxia and Bahadurabad,respectively)reveals contrasting impacts,strongly negatively influencing sediment transport at Bahadurabad.These findings highlight the significance of spatial variability and climatic influences on sediment dynamics,underscoring the necessity for site-specific management strategies.The sediment rating curve(SRC)analysis reveals a strong relationship between sediment and discharge(R^(2)=0.88)at Nuxia and a relatively weaker relationship(R^(2)=0.14)at Bahadurabad,which demonstrates a lower sedimentdischarge coupling that could be affected by downstream factors such as sediment deposition,channel morphology,and anthropogenic activities.This study offers valuable insights into sediment-water dynamics,highlighting the importance of understanding nonlinear relationships in the Brahmaputra River.展开更多
The special columnar jointed structure endows rocks with significant anisotropy,accurately grasping the strength and deformation properties of a columnar jointed rock mass(CJRM)under complex geological conditions is c...The special columnar jointed structure endows rocks with significant anisotropy,accurately grasping the strength and deformation properties of a columnar jointed rock mass(CJRM)under complex geological conditions is crucial for related engineering safety.Combined with the irregular jointed networks observed in the field,artificial irregular CJRM(ICJRM)samples with various inclination angles were prepared for triaxial tests.The results showed that the increase in confining pressure can enhance the ability of the ICJRM to resist deformation and failure,and reduce the deformation and strength anisotropic degrees.Considering the field stress situation,the engineering parts with an inclination angle of 30°−45°need to be taken seriously.Four typical failure modes were identified,and the sample with an inclination angle of 15°showed the same failure behavior as the field CJRM.Traditional and improved joint factor methods were used to establish empirical relationships for predicting the strength and deformation of CJRM under triaxial stress.Since the improved joint factor method can reflect the unique structure of CJRM,the predictive ability of the empirical relationship based on the improved method is better than that based on the traditional joint factor method.展开更多
Given the scarcity of Satellite Frequency and Orbit(SFO)resources,it holds paramount importance to establish a comprehensive knowledge graph of SFO field(SFO-KG)and employ knowledge reasoning technology to automatical...Given the scarcity of Satellite Frequency and Orbit(SFO)resources,it holds paramount importance to establish a comprehensive knowledge graph of SFO field(SFO-KG)and employ knowledge reasoning technology to automatically mine available SFO resources.An essential aspect of constructing SFO-KG is the extraction of Chinese entity relations.Unfortunately,there is currently no publicly available Chinese SFO entity Relation Extraction(RE)dataset.Moreover,publicly available SFO text data contain numerous NA(representing for“No Answer”)relation category sentences that resemble other relation sentences and pose challenges in accurate classification,resulting in low recall and precision for the NA relation category in entity RE.Consequently,this issue adversely affects both the accuracy of constructing the knowledge graph and the efficiency of RE processes.To address these challenges,this paper proposes a method for extracting Chinese SFO text entity relations based on dynamic integrated learning.This method includes the construction of a manually annotated Chinese SFO entity RE dataset and a classifier combining features of SFO resource data.The proposed approach combines integrated learning and pre-training models,specifically utilizing Bidirectional Encoder Representation from Transformers(BERT).In addition,it incorporates one-class classification,attention mechanisms,and dynamic feedback mechanisms to improve the performance of the RE model.Experimental results show that the proposed method outperforms the traditional methods in terms of F1 value when extracting entity relations from both balanced and long-tailed datasets.展开更多
To reduce the spatial simulation error generated by the finite difference method,previous researchers compute the optimal finite-difference weights always by minimizing the error of spatial dispersion relation.However...To reduce the spatial simulation error generated by the finite difference method,previous researchers compute the optimal finite-difference weights always by minimizing the error of spatial dispersion relation.However,we prove that the spatial simulation error of the finite difference method is associated with the dot product of the spatial dispersion relation of the finite-difference weights and the spectrum of the seismic wavefield.Based on the dot product relation,we construct a L_(2) norm cost function to minimize spatial simulation error.For solving this optimization problem,the seismic wavefield infor-mation in wavenumber region is necessary.Nevertheless,the seismic wavefield is generally obtained by costly forward modeling techniques.To reduce the computational cost,we substitute the spectrum of the seismic wavelet for the spectrum of the seismic wavefield,as the seismic wavelet plays a key role in determining the seismic wavefield.In solving the optimization problem,we design an exhaustive search method to obtain the solution of the L_(2) norm optimization problem.After solving the optimization problem,we are able to achieve the finite-difference weights that minimize spatial simulation error.In theoretical error analyses,the finite-difference weights from the proposed method can output more accurate simulation results compared to those from previous optimization algorithms.Furthermore,we validate our method through numerical tests with synthetic models,which encompass homogenous/inhomogeneous media as well as isotropic and anisotropic media.展开更多
The Guqin art form is one of China’s oldest musical traditions and is recognized as a significant part of the world’s intangible cultural heritage.Numerous ancient scores have survived to the present day,but only a ...The Guqin art form is one of China’s oldest musical traditions and is recognized as a significant part of the world’s intangible cultural heritage.Numerous ancient scores have survived to the present day,but only a select few have been adapted for contemporary music.While ancient Guqin scores can be translated into modern numbered or staff notation,their rhythmic elements cannot be accurately replicated.The process of converting these scores into a simplified Guqin notation presents challenges,particularly in selecting appropriate fingerings.To address the issues related to playing ancient scores and transferring new ones,this paper introduces a triple representation method for Guqin score knowledge using knowledge mapping technology.It transforms the simplified Guqin notation into a text format,exemplified by the Ming Dynasty’s“Magic Secret Score.”A computer-editable text corpus of Guqin is created,and various tags are applied to the text.A word cloud visualization of the“Magic Secret Score”text spectrum is generated using a word cloud tool.The frequency of different right-hand fingerings in the“Magic Secret Score”is analyzed.By examining the temporal characteristics of the music,the paper extracts the timing relationships of right-hand fingerings from the text corpus and identifies various performance templates using the KMP pattern matching algorithm.Specifically,it analyzes 64 different right-hand finger techniques.Additionally,the frequency of string combinations in the“Magic Secret Score”is recorded,providing essential guidelines for future intelligent music transfer reasoning.The experimental findings indicate that there are specific constraints on the timing of fingerings and string usage in musical tones,with the maximum length of reusable fingering timing templates being no more than 25.展开更多
It is known that monotone recurrence relations can induce a class of twist homeomorphisms on the high-dimensional cylinder,which is an extension of the class of monotone twist maps on the annulus or two-dimensional cy...It is known that monotone recurrence relations can induce a class of twist homeomorphisms on the high-dimensional cylinder,which is an extension of the class of monotone twist maps on the annulus or two-dimensional cylinder.By constructing a bounded solution of the monotone recurrence relation,the main conclusion in this paper is acquired:The induced homeomorphism has Birkhoff orbits provided there is a compact forward-invariant set.Therefore,it generalizes Angenent's results in low-dimensional cases.展开更多
The present study develops a data-based compact model for the prediction of the fluid temperature evolution in district heating-and-cooling pipeline networks.This model is based on an existing“reduced-order model”by...The present study develops a data-based compact model for the prediction of the fluid temperature evolution in district heating-and-cooling pipeline networks.This model is based on an existing“reduced-order model”by the authors obtained from reduction of the“full-order model”describing the spatio-temporal energy balance for each pipe segment to a semi-analytical input-output relation between the pipe outlet temperature and the pipe inlet and ground temperatures.The proposed model(denoted XROM)expands on the original reduced-order model by incorporating variable mass flux as an additional input and thus greatly increases its practical relevance.The XROM represents variable mass flux by step-wise switching between mass-flux levels and thereby induces a prediction error relative to the true full-order model evolution after each switching.Theoretical analysis rigorously demonstrates that this error always decays and the XROM invariably converges on the full-order model evolution and,consequently,affords the same prediction accuracy.Performance analyses reveal that prediction errors are restricted to short“convergence intervals”after each mass-flux switching and the XROM therefore can handle substantially faster operating schemes than the current ones based on hourly monitoring and control.Convergence intervals of O(minutes)are namely typically sufficient-and thus switching frequencies up to O(minutes 1)permissible during dynamic operation and control actions-for reliable predictions.Quantification of these convergence intervals by an easy-to-use empirical relation furthermore enables a priori determination of the conditions for reliable predictions.Moreover,the XROM can capture the full 3D system dynamics(provided incompressible flow and heat-transfer mechanisms depending linearly on temperature)versus the essentially 1D approximation of current compact pipe models yet at similar computational cost.These attributes advance(parts of)district heating and cooling networks demanding prediction accuracies beyond 1D as its primary application area.This makes the XROM complementary to said pipe models and thereby expands the modelling capabilities for handling the growing complexity of(next-generation)networks.展开更多
We design dynamical Casimir arrays(DCA)consisting of giant atoms and coupled resonator waveguides(CRWs)to investigate the Einstein–Podolsky–Rosen(EPR)steering at finite temperatures.Our designed system exhibits an a...We design dynamical Casimir arrays(DCA)consisting of giant atoms and coupled resonator waveguides(CRWs)to investigate the Einstein–Podolsky–Rosen(EPR)steering at finite temperatures.Our designed system exhibits an asymmetry in its structure,which is caused by the differences in the sizes and the coupling positions of the giant atoms.The system achieves different types of EPR steering and the reversal of one-way EPR steering by modulating parameters.Furthermore,the symmetry and asymmetry of the system structure,in their responses to parameter modulation,both reveal the asymmetry of EPR steering.In this process,we discover that with the increase in temperature,different types of steering can be transferred from Casimir photons to giant atoms.We also achieve the monogamy of the multipartite system.These results provide important assistance for secure quantum communication,and further intuitively validating the asymmetry of EPR steering from multiple perspectives.展开更多
Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to vari...Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.展开更多
With the unprecedented prevalence of Industrial Internet of Things(IIoT)and 5G technology,various applications supported by industrial communication systems have generated exponentially increased processing tasks,whic...With the unprecedented prevalence of Industrial Internet of Things(IIoT)and 5G technology,various applications supported by industrial communication systems have generated exponentially increased processing tasks,which makes task assignment inefficient due to insufficient workers.In this paper,an Intelligent and Trustworthy task assignment method based on Trust and Social relations(ITTS)is proposed for scenarios with many tasks and few workers.Specifically,ITTS first makes initial assignments based on trust and social influences,thereby transforming the complex large-scale industrial task assignment of the platform into the small-scale task assignment for each worker.Then,an intelligent Q-decision mechanism based on workers'social relation is proposed,which adopts the first-exploration-then-utilization principle to allocate tasks.Only when a worker cannot cope with the assigned tasks,it initiates dynamic worker recruitment,thus effectively solving the worker shortage problem as well as the cold start issue.More importantly,we consider trust and security issues,and evaluate the trust and social circles of workers by accumulating task feedback,to provide the platform a reference for worker recruitment,thereby creating a high-quality worker pool.Finally,extensive simulations demonstrate ITTS outperforms two benchmark methods by increasing task completion rates by 56.49%-61.53%and profit by 42.34%-47.19%.展开更多
文摘This article broadens terminology and approaches that continue to advance time modelling within a relationalist framework. Time is modeled as a single dimension, flowing continuously through independent privileged points. Introduced as absolute point-time, abstract continuous time is a backdrop for concrete relational-based time that is finite and discrete, bound to the limits of a real-world system. We discuss how discrete signals at a point are used to temporally anchor zero-temporal points [t = 0] in linear time. Object-oriented temporal line elements, flanked by temporal point elements, have a proportional geometric identity quantifiable by a standard unit system and can be mapped on a natural number line. Durations, line elements, are divisible into ordered unit ratio elements using ancient timekeeping formulas. The divisional structure provides temporal classes for rotational (Rt24t) and orbital (Rt18) sample periods, as well as a more general temporal class (Rt12) applicable to either sample or frame periods. We introduce notation for additive cyclic counts of sample periods, including divisional units, for calendar-like formatting. For system modeling, unit structures with dihedral symmetry, group order, and numerical order are shown to be applicable to Euclidean modelling. We introduce new functions for bijective and non-bijective mapping, modular arithmetic for cyclic-based time counts, and a novel formula relating to a subgroup of Pythagorean triples, preserving dihedral n-polygon symmetries. This article presents a new approach to model time in a relationalistic framework.
文摘The present technical paper outlines the details of the controlled blasting techniques used to optimize blasting pattern for excavation of hard rock near the Bhira Earthen Dam in Maharashtra,India.In this connection,a series of experimental blasts were conducted by adjusting various blast design parameters at project site.The safe charge weight per delay was kept between 0.125 and 0.375 kg.The outcomes of these experimental blasts were analyzed to recommend optimized blasting patterns and methods for the overall excavation process during actual blasting operations.Blast design parameters,including the maximum quantity of explosive per delay,hole depth,burden and spacing between holes were optimized by using a site-specific attenuation equation,taking into account the proximity of the dam and tunnel from the blasting area.Peak particle velocity(PPV)level of 10 mm/s and 50 mm/s respectively were adopted as the safe vibration level for ensuring safety of the Bhira Earthen Dam and the nearby tunnel from the adverse effects of blast vibrations by analyzing the dominant frequency of ground vibrations observed and also by reviewing various international standards.Frequency of the ground vibrations observed on the dam and tunnel from majority of the blasts was found to be more than 10 Hz and 50 Hz respectively.During the entire period of blasting,the blast vibrations were recorded to be far lower than the safe vibration level set for these structures.Maximum Vibration level of about 0.8 mm/s and 35 mm/s were observed on dam and tunnel respectively which are far lower than the safe vibration level adopted for these structures.Hence,the entire excavation work was completed successfully and safely,without endangering the safety of dam or tunnel.
基金Supported by the National Natural Science Foundation of China(Nos.12271439,11871398)the National College Students Innovation and Entrepreneurship Training Program(No.201910699173)。
文摘The concept of matching energy was proposed by Gutman and Wagner firstly in 2012. Let G be a simple graph of order n and λ1, λ2, . . . , λn be the zeros of its matching polynomial. The matching energy of a graph G is defined as ME(G) = Pni=1 |λi|. By the famous Coulson’s formula, matching energies can also be calculated by an improper integral depending on a parameter. A k-claw attaching graph Gu(k) refers to the graph obtained by attaching k pendent edges to the graph G at the vertex u, where u is called the root of Gu(k). In this paper, we use some theories of mathematical analysis to obtain a new technique to compare the matching energies of two k-claw attaching graphs Gu(k) and Hv(k) with the same order, that is, limk→∞[ME(Gu(k)) − ME(Hv(k))] = ME(G − u) − ME(H − v). By the technique, we finally determine unicyclic graphs of order n with the 9th to 13th minimal matching energies for all n ≥ 58.
基金funding from Key Areas Science and Technology Research Plan of Xinjiang Production And Construction Corps Financial Science and Technology Plan Project under Grant Agreement No.2023AB048 for the project:Research and Application Demonstration of Data-driven Elderly Care System.
文摘In recent years,with the rapid development of deep learning technology,relational triplet extraction techniques have also achieved groundbreaking progress.Traditional pipeline models have certain limitations due to error propagation.To overcome the limitations of traditional pipeline models,recent research has focused on jointly modeling the two key subtasks-named entity recognition and relation extraction-within a unified framework.To support future research,this paper provides a comprehensive review of recently published studies in the field of relational triplet extraction.The review examines commonly used public datasets for relational triplet extraction techniques and systematically reviews current mainstream joint extraction methods,including joint decoding methods and parameter sharing methods,with joint decoding methods further divided into table filling,tagging,and sequence-to-sequence approaches.In addition,this paper also conducts small-scale replication experiments on models that have performed well in recent years for each method to verify the reproducibility of the code and to compare the performance of different models under uniform conditions.Each method has its own advantages in terms of model design,task handling,and application scenarios,but also faces challenges such as processing complex sentence structures,cross-sentence relation extraction,and adaptability in low-resource environments.Finally,this paper systematically summarizes each method and discusses the future development prospects of joint extraction of relational triples.
文摘The aim of the study is to explore the essential characteristic of tourism,transport,and terrorism and to highlight the connection between them.Tourism as a phenomenon is related to the question“why do people travel?”.The answer to this question requires clarifying a number of sociological and psychological features such as leisure and budget time travel,motivation for travel,psychological benefits,fashion,terrorism,and more.Tourism is a socio-economic and cultural phenomenon that has multiple manifestations.It is one of the factors and driving forces of globalization.Its operation and development leads to the emergence of different economic,socio-cultural,environmental,political,and health effects,making it an indispensable part of modern life.
文摘Dispersion characteristics of magnonic crystals have attracted considerable attention because of the potential applications for spin-wave devices.In this work,we investigated the strain-manipulated dispersion characteristics of magnonic crystals with Dzyaloshinskii–Moriya interaction(DMI)and discussed the potential applications in spin-wave devices.Here,the ground states and stabilities of the magnonic crystals were investigated.Then,the strain-manipulated dispersion characteristics of the magnonic crystals based on domains and skyrmions were studied.The simulation results indicated that,the applied strain could manipulate the band widths and the positions of the allowed frequency bands.Finally,the realization of magnonic crystal heterojunctions and potential applications in spin-wave devices,such as filters,diodes,and transistors based on strain-manipulated magnonic crystals were proposed.Our research provides a theoretical foundation for designing tunable spin-wave devices based on strain-manipulated magnonic crystals with DMI.
基金financially supported by the National Natural Science Foundation of China(Nos.52321001,52322105,52130002,U2241245,52261135634 and 52371084)the Youth Innovation Promotion Association(CAS,No.2021192)the IMR Innovation Fund(No.2023-ZD01).
文摘Metastable β titanium alloy is an ideal material for lightweight and high strength due to its excellent comprehensive mechanical properties.However,overcoming the trade-off relation between strength and ductility remains a significant challenge.In this study,the mechanical properties of Ti-38644 alloy were optimized by introducing a heterogeneous bi-grain bi-lamella(BG-BL)structure through a well-designed combination of rolling,drawing and heat treatment.The results demonstrate that the present BG-BL Ti-38644 alloy shows a tensile strength of~1500 MPa and a total elongation of 18%.In particular,the high strength-elongation combination of the BG-BL Ti-38644 alloy breakthroughs the trade-off relation in all the titanium alloys available.The recrystallized grains with low dislocation enhance the ductility of the Ti-38644 alloy,while the highly distorted elongated grains mainly contribute to the high strength.The present study provides a new principle for designing Ti alloys with superior strength and ductility.
基金The National Key R&D Program of China under contract No.2024YFF0506800the National Natural Science Foundation of China under contract No.T2122012.
文摘On April 3,2024,a magnitude Mw 7.4 earthquake struck the city of Hualien,Taiwan,China,causing casualties and immense damage.This earthquake triggered a tsunami,which was recorded by the nearby tide gauges and Deep-Ocean Assessment and Reporting of Tsunamis(DART)buoys.These recordings are valuable for evaluating the tsunami source and quantifying the tsunami characteristics.In this study,we conduct tsunami simulations based on three earthquake source models,and analyze their reliability by comparing the computed results with observed waveforms.The evaluated source models are the United States Geological Survey(USGS)finite-fault model,and two uniform slip models using different scaling relations.The tsunami waves generated by each source are simulated with a nonhydrostatic tsunami model,which accounts for the effects of wave dispersion.The computed tsunami arrival times and wave heights are compared to the observed data and show high consistency,indicating that the magnitude and location of the earthquake source are well estimated.Also,the three source models with different rupture area and average slip lead to almost the same tsunami waves at each station,which suggests that earthquake rupture details have limited impact on far-filed tsunami records.It is also found that wave dispersion effects in this event are negligible at most stations.The findings are useful for tsunami warning.For fast warning purposes,it is practically useful to adopt simplified uniform slip models,which are able to predict the tsunami arrival time and wave height relatively well without knowing the earthquake source details.
基金supported by Liuchuang Program of Chongqing Municipality(cx2022038)the Fundamental Research Funds for the Central Universities(2022CDJQY-013)the Graduate Research and Innovation Foundation of Chongqing,China(CYB22005).
文摘While early transition metal-based materials,such as MXene,has emerged as an efficient catalyst for the Mg-based hydrogen storage materials,their strong interaction with hydrogen resulted in the high hydrogen diffusion barrier,hindering further improvement of catalytic activity.A MXene is characterized by rich anionic groups on its surface,significantly affecting electronic and catalytic functionalities.Using Nb_(2)CT_(x)as an example,we herein illustrate the critical role of anionic T_(x)defects on controlling hydrogen dissociation and diffusion processes in Mg-based hydrogen storage materials.The hydrogen desorption properties of MgH_(2)can be significantly enhanced by utilizing T_(x)controllable Nb_(2)CT_(x),and it can release 3.57 wt.%hydrogen within 10 min under 240℃with the reduced dehydrogenation activation barrier.It also realized stable de/hydrogenation reactions for at least 50 cycles.DFT studies combined with kinetic analysis revealed that the catalyst‒hydrogen interaction could be systematically controlled by optimizing surface T_(x)defect density,accelerating the hydrogen dissociation and diffusion processes at the same time.These results demonstrate that the T_(x)defects serve as the effective catalytically active centers of Nb_(2)CT_(x),offering a flexible catalyst design guideline.
基金funded by the National Key Technology R&D Program of China under Grant No.2021YFD2100605the National Natural Science Foundation of China under Grant No.62433002+1 种基金the Project of Construction and Support for High-Level Innovative Teams of Beijing Municipal Institutions under Grant No.BPHR20220104Beijing Scholars Program under Grant No.099.
文摘Entity relation extraction,a fundamental and essential task in natural language processing(NLP),has garnered significant attention over an extended period.,aiming to extract the core of semantic knowledge from unstructured text,i.e.,entities and the relations between them.At present,the main dilemma of Chinese entity relation extraction research lies in nested entities,relation overlap,and lack of entity relation interaction.This dilemma is particularly prominent in complex knowledge extraction tasks with high-density knowledge,imprecise syntactic structure,and lack of semantic roles.To address these challenges,this paper presents an innovative“character-level”Chinese part-of-speech(CN-POS)tagging approach and incorporates part-of-speech(POS)information into the pre-trained model,aiming to improve its semantic understanding and syntactic information processing capabilities.Additionally,A relation reference filling mechanism(RF)is proposed to enhance the semantic interaction between relations and entities,utilize relations to guide entity modeling,improve the boundary prediction ability of entity models for nested entity phenomena,and increase the cascading accuracy of entity-relation triples.Meanwhile,the“Queue”sub-task connection strategy is adopted to alleviate triplet cascading errors caused by overlapping relations,and a Syntax-enhanced entity relation extraction model(SE-RE)is constructed.The model showed excellent performance on the self-constructed E-commerce Product Information dataset(EPI)in this article.The results demonstrate that integrating POS enhancement into the pre-trained encoding model significantly boosts the performance of entity relation extraction models compared to baseline methods.Specifically,the F1-score fluctuation in subtasks caused by error accumulation was reduced by 3.21%,while the F1-score for entity-relation triplet extraction improved by 1.91%.
基金jointly supported by the Second Tibetan Plateau Scientific Expedition and Research Program(Grant No.2019QZKK0902)National Natural Science Foundation of China(NSFC)project(Grant No.42305178)+1 种基金the Key R&D Program of Tibet Autonomous Region(Grant No.XZ202301ZY0039G)the Science and Technology Research Program of Institute of Mountain Hazards and Environment,Chinese Academy of Sciences(Grant No.IMHEZDRW-01)。
文摘Understanding the relationship between sediment and discharge is crucial for effective river management and water-sediment modeling,especially in the Brahmaputra River,one of the large transboundary rivers with high sediment and discharge variability in South Asia.Current knowledge of sediment-water relations is constrained by limited data,hindering effective transboundary river management.Using multivariate linear regression,climate elasticity coefficient,and traditional sediment rating curve,this study is designed to compare the sediment-water relations of the upstream(Nuxia)and the downstream(Bahadurabad).The results reveal significant variability between the two stations.In the upstream Nuxia,the simulation strongly correlates with observed suspended sediment load(SSL)and discharge(Q)(Pearson's r of 0.62 and 0.68,respectively).Conversely,at downstream Bahadurabad,weaker correlations(r=0.31 for sediment and r=0.51 for discharge simulation)indicate a reduced relation.This contrast reflects the non-linear nature of sediment-discharge coupling along the river continuum,shaped by both climatic and anthropogenic influences.Elasticity(ε)analysis highlights the dominant role of precipitation in shaping sediment-water dynamics(εP-SSL=2.53,εP-Q=1.01)at Nuxia,while Bahadurabad(εP-SSL=0.41,εP-Q=0.82)reflects a reduced sensitivity,possibly due to sediment retention along the floodplain.Air temperature elasticity(εT-SSL,-0.15&-3.06 at Nuxia and Bahadurabad,respectively)reveals contrasting impacts,strongly negatively influencing sediment transport at Bahadurabad.These findings highlight the significance of spatial variability and climatic influences on sediment dynamics,underscoring the necessity for site-specific management strategies.The sediment rating curve(SRC)analysis reveals a strong relationship between sediment and discharge(R^(2)=0.88)at Nuxia and a relatively weaker relationship(R^(2)=0.14)at Bahadurabad,which demonstrates a lower sedimentdischarge coupling that could be affected by downstream factors such as sediment deposition,channel morphology,and anthropogenic activities.This study offers valuable insights into sediment-water dynamics,highlighting the importance of understanding nonlinear relationships in the Brahmaputra River.
基金Projects(42307192,41831278)supported by the National Natural Science Foundation of ChinaProject(CKWV20231175/KY)supported by the CRSRI Open Research Program,China。
文摘The special columnar jointed structure endows rocks with significant anisotropy,accurately grasping the strength and deformation properties of a columnar jointed rock mass(CJRM)under complex geological conditions is crucial for related engineering safety.Combined with the irregular jointed networks observed in the field,artificial irregular CJRM(ICJRM)samples with various inclination angles were prepared for triaxial tests.The results showed that the increase in confining pressure can enhance the ability of the ICJRM to resist deformation and failure,and reduce the deformation and strength anisotropic degrees.Considering the field stress situation,the engineering parts with an inclination angle of 30°−45°need to be taken seriously.Four typical failure modes were identified,and the sample with an inclination angle of 15°showed the same failure behavior as the field CJRM.Traditional and improved joint factor methods were used to establish empirical relationships for predicting the strength and deformation of CJRM under triaxial stress.Since the improved joint factor method can reflect the unique structure of CJRM,the predictive ability of the empirical relationship based on the improved method is better than that based on the traditional joint factor method.
文摘Given the scarcity of Satellite Frequency and Orbit(SFO)resources,it holds paramount importance to establish a comprehensive knowledge graph of SFO field(SFO-KG)and employ knowledge reasoning technology to automatically mine available SFO resources.An essential aspect of constructing SFO-KG is the extraction of Chinese entity relations.Unfortunately,there is currently no publicly available Chinese SFO entity Relation Extraction(RE)dataset.Moreover,publicly available SFO text data contain numerous NA(representing for“No Answer”)relation category sentences that resemble other relation sentences and pose challenges in accurate classification,resulting in low recall and precision for the NA relation category in entity RE.Consequently,this issue adversely affects both the accuracy of constructing the knowledge graph and the efficiency of RE processes.To address these challenges,this paper proposes a method for extracting Chinese SFO text entity relations based on dynamic integrated learning.This method includes the construction of a manually annotated Chinese SFO entity RE dataset and a classifier combining features of SFO resource data.The proposed approach combines integrated learning and pre-training models,specifically utilizing Bidirectional Encoder Representation from Transformers(BERT).In addition,it incorporates one-class classification,attention mechanisms,and dynamic feedback mechanisms to improve the performance of the RE model.Experimental results show that the proposed method outperforms the traditional methods in terms of F1 value when extracting entity relations from both balanced and long-tailed datasets.
基金supported by the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(No.2021QNLM020001)the Major Scientific and Technological Projects of Shandong Energy Group(No.SNKJ2022A06-R23)+1 种基金the Funds of Creative Research Groups of China(No.41821002)the Major Scientific and Technological Projects of CNPC(No.ZD2019-183-003).
文摘To reduce the spatial simulation error generated by the finite difference method,previous researchers compute the optimal finite-difference weights always by minimizing the error of spatial dispersion relation.However,we prove that the spatial simulation error of the finite difference method is associated with the dot product of the spatial dispersion relation of the finite-difference weights and the spectrum of the seismic wavefield.Based on the dot product relation,we construct a L_(2) norm cost function to minimize spatial simulation error.For solving this optimization problem,the seismic wavefield infor-mation in wavenumber region is necessary.Nevertheless,the seismic wavefield is generally obtained by costly forward modeling techniques.To reduce the computational cost,we substitute the spectrum of the seismic wavelet for the spectrum of the seismic wavefield,as the seismic wavelet plays a key role in determining the seismic wavefield.In solving the optimization problem,we design an exhaustive search method to obtain the solution of the L_(2) norm optimization problem.After solving the optimization problem,we are able to achieve the finite-difference weights that minimize spatial simulation error.In theoretical error analyses,the finite-difference weights from the proposed method can output more accurate simulation results compared to those from previous optimization algorithms.Furthermore,we validate our method through numerical tests with synthetic models,which encompass homogenous/inhomogeneous media as well as isotropic and anisotropic media.
基金supported by the 2024 special project of the Zhejiang Provincial Higher Education Association,“Research on the Application of Artificial Intelligence in Educational Teaching”(No.KT2024441)in China.
文摘The Guqin art form is one of China’s oldest musical traditions and is recognized as a significant part of the world’s intangible cultural heritage.Numerous ancient scores have survived to the present day,but only a select few have been adapted for contemporary music.While ancient Guqin scores can be translated into modern numbered or staff notation,their rhythmic elements cannot be accurately replicated.The process of converting these scores into a simplified Guqin notation presents challenges,particularly in selecting appropriate fingerings.To address the issues related to playing ancient scores and transferring new ones,this paper introduces a triple representation method for Guqin score knowledge using knowledge mapping technology.It transforms the simplified Guqin notation into a text format,exemplified by the Ming Dynasty’s“Magic Secret Score.”A computer-editable text corpus of Guqin is created,and various tags are applied to the text.A word cloud visualization of the“Magic Secret Score”text spectrum is generated using a word cloud tool.The frequency of different right-hand fingerings in the“Magic Secret Score”is analyzed.By examining the temporal characteristics of the music,the paper extracts the timing relationships of right-hand fingerings from the text corpus and identifies various performance templates using the KMP pattern matching algorithm.Specifically,it analyzes 64 different right-hand finger techniques.Additionally,the frequency of string combinations in the“Magic Secret Score”is recorded,providing essential guidelines for future intelligent music transfer reasoning.The experimental findings indicate that there are specific constraints on the timing of fingerings and string usage in musical tones,with the maximum length of reusable fingering timing templates being no more than 25.
基金Supported by the National Natural Science Foundation of China(12201446)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(22KJB110005)the Shuangchuang Program of Jiangsu Province(JSSCBS20220898)。
文摘It is known that monotone recurrence relations can induce a class of twist homeomorphisms on the high-dimensional cylinder,which is an extension of the class of monotone twist maps on the annulus or two-dimensional cylinder.By constructing a bounded solution of the monotone recurrence relation,the main conclusion in this paper is acquired:The induced homeomorphism has Birkhoff orbits provided there is a compact forward-invariant set.Therefore,it generalizes Angenent's results in low-dimensional cases.
文摘The present study develops a data-based compact model for the prediction of the fluid temperature evolution in district heating-and-cooling pipeline networks.This model is based on an existing“reduced-order model”by the authors obtained from reduction of the“full-order model”describing the spatio-temporal energy balance for each pipe segment to a semi-analytical input-output relation between the pipe outlet temperature and the pipe inlet and ground temperatures.The proposed model(denoted XROM)expands on the original reduced-order model by incorporating variable mass flux as an additional input and thus greatly increases its practical relevance.The XROM represents variable mass flux by step-wise switching between mass-flux levels and thereby induces a prediction error relative to the true full-order model evolution after each switching.Theoretical analysis rigorously demonstrates that this error always decays and the XROM invariably converges on the full-order model evolution and,consequently,affords the same prediction accuracy.Performance analyses reveal that prediction errors are restricted to short“convergence intervals”after each mass-flux switching and the XROM therefore can handle substantially faster operating schemes than the current ones based on hourly monitoring and control.Convergence intervals of O(minutes)are namely typically sufficient-and thus switching frequencies up to O(minutes 1)permissible during dynamic operation and control actions-for reliable predictions.Quantification of these convergence intervals by an easy-to-use empirical relation furthermore enables a priori determination of the conditions for reliable predictions.Moreover,the XROM can capture the full 3D system dynamics(provided incompressible flow and heat-transfer mechanisms depending linearly on temperature)versus the essentially 1D approximation of current compact pipe models yet at similar computational cost.These attributes advance(parts of)district heating and cooling networks demanding prediction accuracies beyond 1D as its primary application area.This makes the XROM complementary to said pipe models and thereby expands the modelling capabilities for handling the growing complexity of(next-generation)networks.
基金Project supported by the Education Department of Jilin Province,China(Grant No.JJKH20231291KJ)。
文摘We design dynamical Casimir arrays(DCA)consisting of giant atoms and coupled resonator waveguides(CRWs)to investigate the Einstein–Podolsky–Rosen(EPR)steering at finite temperatures.Our designed system exhibits an asymmetry in its structure,which is caused by the differences in the sizes and the coupling positions of the giant atoms.The system achieves different types of EPR steering and the reversal of one-way EPR steering by modulating parameters.Furthermore,the symmetry and asymmetry of the system structure,in their responses to parameter modulation,both reveal the asymmetry of EPR steering.In this process,we discover that with the increase in temperature,different types of steering can be transferred from Casimir photons to giant atoms.We also achieve the monogamy of the multipartite system.These results provide important assistance for secure quantum communication,and further intuitively validating the asymmetry of EPR steering from multiple perspectives.
文摘Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.
基金supported by the National Natural Science Foundation of China under Grant No.62072475 and No.62302062in part by the Hunan Provincial Natural Science Foundation of China under Grant Number 2023JJ40081。
文摘With the unprecedented prevalence of Industrial Internet of Things(IIoT)and 5G technology,various applications supported by industrial communication systems have generated exponentially increased processing tasks,which makes task assignment inefficient due to insufficient workers.In this paper,an Intelligent and Trustworthy task assignment method based on Trust and Social relations(ITTS)is proposed for scenarios with many tasks and few workers.Specifically,ITTS first makes initial assignments based on trust and social influences,thereby transforming the complex large-scale industrial task assignment of the platform into the small-scale task assignment for each worker.Then,an intelligent Q-decision mechanism based on workers'social relation is proposed,which adopts the first-exploration-then-utilization principle to allocate tasks.Only when a worker cannot cope with the assigned tasks,it initiates dynamic worker recruitment,thus effectively solving the worker shortage problem as well as the cold start issue.More importantly,we consider trust and security issues,and evaluate the trust and social circles of workers by accumulating task feedback,to provide the platform a reference for worker recruitment,thereby creating a high-quality worker pool.Finally,extensive simulations demonstrate ITTS outperforms two benchmark methods by increasing task completion rates by 56.49%-61.53%and profit by 42.34%-47.19%.
