Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

Effective Crowd Anomaly Detection Through Spatio-temporal Texture Analysis

Abnormal crowd behaviors in high density situations can pose great danger to public safety. Despite the extensive installation of closed-circuit television(CCTV) cameras, it is still difficult to achieve real-time alerts and automated responses from current systems. Two major breakthroughs have been reported in this research. Firstly, a spatial-temporal texture extraction algorithm is developed. This algorithm is able to effectively extract video textures with abundant crowd motion details. It is through adopting Gaborfiltered textures with the highest information entropy values. Secondly, a novel scheme for defining crowd motion patterns(signatures)is devised to identify abnormal behaviors in the crowd by employing an enhanced gray level co-occurrence matrix model. In the experiments, various classic classifiers are utilized to benchmark the performance of the proposed method. The results obtained exhibit detection and accuracy rates which are, overall, superior to other techniques.

Achieving high ductility and low in-plane anisotropy in magnesium alloy through a novel texture design strategy

Texture regulation is a prominent method to modify the mechanical properties and anisotropy of magnesium alloy.In this work,the Mg-1Al-0.3Ca-0.5Mn-0.2Gd(wt.%)alloy sheet with TD-tilted and circular texture was fabricated by unidirectional rolling(UR)and multidirectional rolling(MR)method,respectively.Unlike generating a strong in-plane mechanical anisotropy in conventional TD-tilted texture,the novel circular texture sample possessed a weak in-plane yield anisotropy.This can be rationalized by the similar proportion of soft grains with favorable orientation for basalslip and{10.12}tensile twinning during the uniaxial tension of circular-texture sample along different directions.Moreover,compared with the TD-tilted texture,the circular texture improved the elongation to failure both along the rolling direction(RD)and transverse direction(TD).By quasi-in-situ EBSD-assisted slip trace analysis,higher activation of basal slip was observed in the circular-texture sample during RD tension,contributing to its excellent ductility.When loading along the TD,the TD-tilted texture promoted the activation of{10.12}tensile twins significantly,thus providing nucleation sites for cracks and deteriorating the ductility.This research may shed new insights into the development of formable and ductile Mg alloy sheets by texture modification.

The Mechanism of Cube Texture Formation in Ni-7 at%W Substrate

In order to obtain the sharp cube texture,a new process,the intermediate annealing rolling technique,has been introduced to prepare the Ni7W substrate.In this paper,a cubic texture content up to 98.5%within 10°of the standard cubic orientation is obtained in the final substrate and the influence of this improved rolling technique on the cube texture formation has been discussed.The results show that the increased cube texture in the Ni7W substrate is caused by the optimized deformation texture and the increased nucleated fraction of the cube grains.

Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

Recent advances in spatio-temporally controllable systems for management of glioma

Malignant glioma remains one of the most aggressive intracranial tumors with devastating clinical outcomes despite the great advances in conventional treatment approaches,including surgery and chemotherapy.Spatio-temporally controllable approaches to glioma are now being actively investigated due to the preponderance,including spatio-temporal adjustability,minimally invasive,repetitive properties,etc.External stimuli can be readily controlled by adjusting the site and density of stimuli to exert the cytotoxic on glioma tissue and avoid undesired injury to normal tissues.It is worth noting that the removability of external stimuli allows for on-demand treatment,which effectively reduces the occurrence of side effects.In this review,we highlight recent advancements in drug delivery systems for spatio-temporally controllable treatments of glioma,focusing on the mechanisms and design principles of sensitizers utilized in these controllable therapies.Moreover,the potential challenges regarding spatio-temporally controllable therapy for glioma are also described,aiming to provide insights into future advancements in this field and their potential clinical applications.

Epidemic Characteristics and Spatio-Temporal Patterns of HFRS in Qingdao City,China,2010-2022

Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingdao City from 2010 to 2022.Descriptive epidemiologic,seasonal decomposition,spatial autocorrelation,and spatio-temporal cluster analyses were performed.Results A total of 2,220 patients with HFRS were reported over the study period,with an average annual incidence of 1.89/100,000 and a case fatality rate of 2.52%.The male:female ratio was 2.8:1.75.3%of patients were aged between 16 and 60 years old,75.3%of patients were farmers,and 11.6%had both“three red”and“three pain”symptoms.The HFRS epidemic showed two-peak seasonality:the primary fall-winter peak and the minor spring peak.The HFRS epidemic presented highly spatially heterogeneous,street/township-level hot spots that were mostly distributed in Huangdao,Pingdu,and Jiaozhou.The spatio-temporal cluster analysis revealed three cluster areas in Qingdao City that were located in the south of Huangdao District during the fall-winter peak.Conclusion The distribution of HFRS in Qingdao exhibited periodic,seasonal,and regional characteristics,with high spatial clustering heterogeneity.The typical symptoms of“three red”and“three pain”in patients with HFRS were not obvious.

Dynamic adaptive spatio-temporal graph network for COVID-19 forecasting

Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 forecasting.However,in previous deep learning models for epidemic forecasting,spatial and temporal variations are captured separately.A unified model is developed to cover all spatio-temporal relations.However,this measure is insufficient for modelling the complex spatio-temporal relations of infectious disease transmission.A dynamic adaptive spatio-temporal graph network(DASTGN)is proposed based on attention mechanisms to improve prediction accuracy.In DASTGN,complex spatio-temporal relations are depicted by adaptively fusing the mixed space-time effects and dynamic space-time dependency structure.This dual-scale model considers the time-specific,space-specific,and direct effects of the propagation process at the fine-grained level.Furthermore,the model characterises impacts from various space-time neighbour blocks under time-varying interventions at the coarse-grained level.The performance comparisons on the three COVID-19 datasets reveal that DASTGN achieves state-of-the-art results with a maximum improvement of 17.092%in the root mean-square error and 11.563%in the mean absolute error.Experimental results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of COVID-19.The spatio-temporal weight matrices learned in each proposed module reveal diffusion patterns in various scenarios.In conclusion,DASTGN has successfully captured the dynamic spatio-temporal variations of COVID-19,and considering multiple dynamic space-time relationships is essential in epidemic forecasting.

Crystal plasticity finite element simulations on extruded Mg-10Gd rod with texture gradient

The mechanical properties of an extruded Mg-10Gd sample, specifically designed for vascular stents, are crucial for predicting its behavior under service conditions. Achieving homogeneous stresses in the hoop direction, essential for characterizing vascular stents, poses challenges in experimental testing based on standard specimens featuring a reduced cross section. This study utilizes an elasto-visco-plastic self-consistent polycrystal model(ΔEVPSC) with the predominant twinning reorientation(PTR) scheme as a numerical tool, offering an alternative to mechanical testing. For verification, various mechanical experiments, such as uniaxial tension, compression, notched-bar tension, three-point bending, and C-ring compression tests, were conducted. The resulting force vs. displacement curves and textures were then compared with those based on the ΔEVPSC model. The computational model's significance is highlighted by simulation results demonstrating that the differential hardening along with a weak strength differential effect observed in the Mg-10Gd sample is a result of the interplay between micromechanical deformation mechanisms and deformation-induced texture evolution. Furthermore, the study highlights that incorporating the axisymmetric texture from the as-received material incorporating the measured texture gradient significantly improves predictive accuracy on the strength in the hoop direction. Ultimately, the findings suggest that the ΔEVPSC model can effectively predict the mechanical behavior resulting from loading scenarios that are impossible to realize experimentally, emphasizing its valuable contribution as a digital twin.

An Intelligent Framework for Resilience Recovery of FANETs with Spatio-Temporal Aggregation and Multi-Head Attention Mechanism

Due to the time-varying topology and possible disturbances in a conflict environment,it is still challenging to maintain the mission performance of flying Ad hoc networks(FANET),which limits the application of Unmanned Aerial Vehicle(UAV)swarms in harsh environments.This paper proposes an intelligent framework to quickly recover the cooperative coveragemission by aggregating the historical spatio-temporal network with the attention mechanism.The mission resilience metric is introduced in conjunction with connectivity and coverage status information to simplify the optimization model.A spatio-temporal node pooling method is proposed to ensure all node location features can be updated after destruction by capturing the temporal network structure.Combined with the corresponding Laplacian matrix as the hyperparameter,a recovery algorithm based on the multi-head attention graph network is designed to achieve rapid recovery.Simulation results showed that the proposed framework can facilitate rapid recovery of the connectivity and coverage more effectively compared to the existing studies.The results demonstrate that the average connectivity and coverage results is improved by 17.92%and 16.96%,respectively compared with the state-of-the-art model.Furthermore,by the ablation study,the contributions of each different improvement are compared.The proposed model can be used to support resilient network design for real-time mission execution.

A texture-modified dessert with high nutritional value designed for people with dysphagia:effect of refrigeration and frozen storage

Dysphagia is commonly associated with malnutrition and an increased choking risk.To overcome these complications,food designed for people with dysphagia should have an appropriate texture and a high nutritional value.In this study,six formulations of a strawberry dessert enriched in protein(calcium caseinate)and fiber(wheat dextrin or inulin)were developed using different hydrocolloids(xanthan gum,carboxymethyl cellulose or modified starch)to provide desirable texture and stability.Nutritional value was calculated and total phenolic content and antioxidant activity of the samples were analyzed.Back-extrusion test,rheological measurements and sensory analysis were performed in refrigerated and frozen samples to characterize their textural and viscoelastic properties.The high content in protein(14.7 g/100 g)and fiber(7.9-8.7 g/100 g)made possible to use the claims“high protein”and“high fiber”.Phytochemicals supplied by strawberries contributed to the antioxidant properties of the dessert.Loss tangent ranged 0.28-0.35 for all the formulations,indicating a weak gel behavior,which could be considered safe to swallow.The formulations with dextrin in combination with carboxymethyl cellulose or xanthan gum seemed to be less susceptible to structural changes during frozen storage.This work provides insights for the development of a nutrient-dense dessert that meets the requirements of people with dysphagia.

Warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography

High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it faces challenge in dense objects tracking and 3D trajectories reconstruction due to the characteristics of small size and dense distribution of fragment swarm.To address these challenges,this work presents a warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography.Firstly,background difference algorithm is utilized to extract the center and area of each fragment in the image sequence.Subsequently,a multi-object tracking(MOT)algorithm using Kalman filtering and Hungarian optimal assignment is developed to realize real-time and robust trajectories tracking of fragment swarm.To reconstruct 3D motion trajectories,a global stereo trajectories matching strategy is presented,which takes advantages of epipolar constraint and continuity constraint to correctly retrieve stereo correspondence followed by 3D trajectories refinement using polynomial fitting.Finally,the simulation and experimental results demonstrate that the proposed method can accurately track the motion trajectories and reconstruct the spatio-temporal distribution of 1.0×10^(3)fragments in a field of view(FOV)of 3.2 m×2.5 m,and the accuracy of the velocity estimation can achieve 98.6%.

Evolution of microstructure and texture of AZ80 magnesium alloy under hot torsion with constant decreasing temperature rate

Hot torsion tests for AZ80 magnesium alloy were carried out in the temperature range of 380℃-260℃,with a constant decreasing temperature rate of 10℃/s in order to weaken the basal texture and refine the grains.The results indicated that the average grain sizes were refined forming gradient structure with increasing specimen radial position from center(12.2-5.4μm),and that the initial basal texture intensity of the extruded magnesium alloy was weakened from 46.2 to 8.3.Furthermore,the extension twins(ETs)could be disintegrated from the twins forming separated twins with smaller sizes.Interestingly,ETs with the same twin variant intersecting with each other could be coalesced forming grains with similar orientation,while ETs with different twin variants were separated by twins boundaries contributing to grain refinement.Moreover,in addition to the conventional continuous dynamic recrystallized(CDRX)grains with 30˚orientation rotated around C-axis of the parent grains,CDRXed grains with 30˚rotation around a-axis and random rotation axis were also discerned.Besides,the CDRX evolution induced twins were also elaborated,exhibiting the complex competition between CDRX and twining.Hot torsion deformation with constant decreasing temperatures rate is an effective way of grain refinement and texture modification.

Unveiling the rolling texture variations ofα-Mg phases in a dual-phase Mg-Li alloy

LZ91 Mg-Li alloy plates with three types of initial texture were rolled by 70%reduction at both room temperature and 200℃to explore the rolling texture formation ofα-Mg phase.The results showed that the rolling texture is largely affected by the initial texture.All the samples exhibited two main texture components as RD-split double peaks texture and TD-split double peaks texture after large strain rolling.The intensity of the two texture components was strongly influenced by the initial orientation and rolling temperature.Extension twinning altered the large-split non-basal orientation to a near basal one at low rolling strain.The basal orientation induced by twinning is unstable,which finally transmitted to the RD-split texture.The strong TD-split texture formed due to slip-induced orientation transition from its initial orientation.The competition between prismatic and basal slip determined the intensity and tilt angle of the TD-split texture.By increasing the rolling temperature,the TD-split texture component was enhanced in all three samples.Limitation of extension twinning behavior and the promotion of prismatic slip at elevated temperature are the main reasons for the difference in hot and cold rolling texture.

A cloud model target damage effectiveness assessment algorithm based on spatio-temporal sequence finite multilayer fragments dispersion

To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.

Self-Attention Spatio-Temporal Deep Collaborative Network for Robust FDIA Detection in Smart Grids

False data injection attack(FDIA)can affect the state estimation of the power grid by tampering with the measured value of the power grid data,and then destroying the stable operation of the smart grid.Existing work usually trains a detection model by fusing the data-driven features from diverse power data streams.Data-driven features,however,cannot effectively capture the differences between noisy data and attack samples.As a result,slight noise disturbances in the power grid may cause a large number of false detections for FDIA attacks.To address this problem,this paper designs a deep collaborative self-attention network to achieve robust FDIA detection,in which the spatio-temporal features of cascaded FDIA attacks are fully integrated.Firstly,a high-order Chebyshev polynomials-based graph convolution module is designed to effectively aggregate the spatio information between grid nodes,and the spatial self-attention mechanism is involved to dynamically assign attention weights to each node,which guides the network to pay more attention to the node information that is conducive to FDIA detection.Furthermore,the bi-directional Long Short-Term Memory(LSTM)network is introduced to conduct time series modeling and long-term dependence analysis for power grid data and utilizes the temporal self-attention mechanism to describe the time correlation of data and assign different weights to different time steps.Our designed deep collaborative network can effectively mine subtle perturbations from spatiotemporal feature information,efficiently distinguish power grid noise from FDIA attacks,and adapt to diverse attack intensities.Extensive experiments demonstrate that our method can obtain an efficient detection performance over actual load data from New York Independent System Operator(NYISO)in IEEE 14,IEEE 39,and IEEE 118 bus systems,and outperforms state-of-the-art FDIA detection schemes in terms of detection accuracy and robustness.

On dry machining of AZ31B magnesium alloy using textured cutting tool inserts

Magnesium alloys have many advantages as lightweight materials for engineering applications,especially in the fields of automotive and aerospace.They undergo extensive cutting or machining while making products out of them.Dry cutting,a sustainable machining method,causes more friction and adhesion at the tool-chip interface.One of the promising solutions to this problem is cutting tool surface texturing,which can reduce tool wear and friction in dry cutting and improve machining performance.This paper aims to investigate the impact of dimple textures(made on the flank face of cutting inserts)on tool wear and chip morphology in the dry machining of AZ31B magnesium alloy.The results show that the cutting speed was the most significant factor affecting tool flank wear,followed by feed rate and cutting depth.The tool wear mechanism was examined using scanning electron microscope(SEM)images and energy dispersive X-ray spectroscopy(EDS)analysis reports,which showed that at low cutting speed,the main wear mechanism was abrasion,while at high speed,it was adhesion.The chips are discontinuous at low cutting speeds,while continuous at high cutting speeds.The dimple textured flank face cutting tools facilitate the dry machining of AZ31B magnesium alloy and contribute to ecological benefits.

Tailoring the texture and mechanical properties of 3%Y_(2)O_(3)p/ZGK200 composites fabricated by unidirectional and cross rolling followed by annealing

3%Y_(2)O_(3)p/ZGK200 composites were subjected to unidirectional rolling(UR)and cross rolling(CR)at 400℃and 350℃followed by annealing at 300℃for 1 h.The microstructure,texture and mechanical properties of rolled and annealed composites were systematically studied.The rolled composites exhibited a heterogeneous microstructure,consisting of deformed grains elongated along rolling direction(RD)and Y_(2)O_(3)particles bands distributed along RD.After annealing,static recrystallization(SRX)occurred and most deformed grains transformed into equiaxed grains.A non-basal texture with two strong T-texture components was obtained after UR while a non-basal elliptical/circle texture with circle multi-peaks was obtained after CR,indicating that rolling path had great influences on texture of the composites.After annealing process,R-texture component disappeared or weakened,as results,a non-basal texture with double peaks tilting from normal direction(ND)to transverse direction(TD)and a more random non-basal texture with circle multi-peaks were obtained for UR and CR composites,respectively.The yield strength of rolled composites after UR showed obvious anisotropy along RD and TD while a low anisotropic yield strength was obtained after CR.Some Y_(2)O_(3)particles broke during rolling.The fracture of the composites was attributed to the existence of Y_(2)O_(3)clusters and interfacial debonding between particles and matrix during tension,as a result,the ductility was not as superior as matrix alloy.

Automatic area estimation of algal blooms in water bodies from UAV images using texture analysis

Algal blooms,the spread of algae on the surface of water bodies,have adverse effects not only on aquatic ecosystems but also on human life.The adverse effects of harmful algal blooms(HABs)necessitate a convenient solution for detection and monitoring.Unmanned aerial vehicles(UAVs)have recently emerged as a tool for algal bloom detection,efficiently providing on-demand images at high spatiotemporal resolutions.This study developed an image processing method for algal bloom area estimation from the aerial images(obtained from the internet)captured using UAVs.As a remote sensing method of HAB detection,analysis,and monitoring,a combination of histogram and texture analyses was used to efficiently estimate the area of HABs.Statistical features like entropy(using the Kullback-Leibler method)were emphasized with the aid of a gray-level co-occurrence matrix.The results showed that the orthogonal images demonstrated fewer errors,and the morphological filter best detected algal blooms in real time,with a precision of 80%.This study provided efficient image processing approaches using on-board UAVs for HAB monitoring.

Effect of forging on the microstructure and texture of a high Nb containing γ-TiAl alloy

The effect of forging on the microstructure and texture evolution of a high Nb containing Ti-45Al-7Nb-0.3W(at.%)alloy was investigated by X-ray diffractometer(XRD),scanning electron microscopy(SEM),and transmission electron microscopy(TEM).The results show that the as-cast alloy is mainly composed of α_(2)/γ lamellar colonies with a mean size of 70μm,but the hot-forged pancake displays a near duplex microstructure(DP).Kinking and bending of lamellar colonies,deformation twinning and dynamic recrystallization(DRX)occur during hot forging.Meanwhile,dense dislocations in theβphase after forging suggest that the high-temperature β phase with a disordered structure is favorable for improving the hot-workability of the alloy.Unlike the common TiAl casting texture,the solidification process of the investigated as-cast alloy with high Nb content is completely via the β phase region,resulting in the formation of a<110>γ fiber texture where the<110>γ aligns parallel to the heat-flow direction.In comparison,the relatively strong<001>and weak<302>texture components in the as-forged alloy are attributed to the deformation twinning.After annealing,static recrystallization occurs at the twin boundary and intersections,which weakens the deformation texture.