The cavity characteristics in liquid-filled containers caused by high-velocity impacts represent an important area of research in hydrodynamic ram phenomena.The dynamic expansion of the cavity induces liquid pressure ...The cavity characteristics in liquid-filled containers caused by high-velocity impacts represent an important area of research in hydrodynamic ram phenomena.The dynamic expansion of the cavity induces liquid pressure variations,potentially causing catastrophic damage to the container.Current studies mainly focus on non-deforming projectiles,such as fragments,with limited exploration of shaped charge jets.In this paper,a uniquely experimental system was designed to record cavity profiles in behind-armor liquid-filled containers subjected to shaped charge jet impacts.The impact process was then numerically reproduced using the explicit simulation program ANSYS LS-DYNA with the Structured Arbitrary Lagrangian-Eulerian(S-ALE)solver.The formation mechanism,along with the dimensional and shape evolution of the cavity was investigated.Additionally,the influence of the impact kinetic energy of the jet on the cavity characteristics was analyzed.The findings reveal that the cavity profile exhibits a conical shape,primarily driven by direct jet impact and inertial effects.The expansion rates of both cavity length and maximum radius increase with jet impact kinetic energy.When the impact kinetic energy is reduced to 28.2 kJ or below,the length-to-diameter ratio of the cavity ultimately stabilizes at approximately 7.展开更多
Liquid-filled containers(LFC)are widely used to store and transport petroleum,chemical reagents,and other resources.As an important target of military strikes and terrorist bombings,LFC are vulnerable to blast waves a...Liquid-filled containers(LFC)are widely used to store and transport petroleum,chemical reagents,and other resources.As an important target of military strikes and terrorist bombings,LFC are vulnerable to blast waves and fragments.To explore the protective effect of polyurea elastomer on LFC,the damage characteristics of polyurea coated liquid-filled container(PLFC)under the combined loading of blast shock wave and fragments were studied experimentally.The microstructure of the polyurea layer was observed by scanning electron microscopy,and the fracture and self-healing phenomena were analyzed.The simulation approach was used to explain the combined blast-and fragments-induced on the PLFC in detail.Finally,the effects of shock wave and fragment alone and in combination on the damage of PLFC were comprehensively compared.Results showed that the polyurea reduces the perforation rate of the fragment to the LFC,and the self-healing phenomenon could also reduce the liquid loss rate inside the container.The polyurea reduces the degree of depression in the center of the LFC,resulting in a decrease in the distance between adjacent fragments penetrating the LFC,and an increase in the probability of transfixion and fracture between holes.Under the close-in blast,the detonation shock wave reached the LFC before the fragment.Polyurea does not all have an enhanced effect on the protection of LFC.The presence of internal water enhances the anti-blast performance of the container,and the hydrodynamic ram(HRAM)formed by the fragment impacting the water aggravated the plastic deformation of the container.The combined action has an enhancement effect on the deformation of the LFC.The depth of the container depression was 27%higher than that of the blast shock wave alone;thus,it cannot be simply summarized as linear superposition.展开更多
Virtualization is an indispensable part of the cloud for the objective of deploying different virtual servers over the same physical layer.However,the increase in the number of applications executing on the repositori...Virtualization is an indispensable part of the cloud for the objective of deploying different virtual servers over the same physical layer.However,the increase in the number of applications executing on the repositories results in increased overload due to the adoption of cloud services.Moreover,the migration of applications on the cloud with optimized resource allocation is a herculean task even though it is employed for minimizing the dilemma of allocating resources.In this paper,a Fire Hawk Optimization enabled Deep Learning Scheme(FHOEDLS)is proposed for minimizing the overload and optimizing the resource allocation on the hybrid cloud container architecture for migrating interoperability based applications This FHOEDLS achieves the load prediction through the utilization of deep CNN-GRU-AM model for attaining resource allocation and better migration of applications.It specifically adopted the Fire Hawk Optimization Algorithm(FHOA)for optimizing the parameters that influence the factors that aid in better interoperable application migration with improved resource allocation and minimized overhead.It considered the factors of resource capacity,transmission cost,demand,and predicted load into account during the formulation of the objective function utilized for resource allocation and application migration.The cloud simulation of this FHOEDLS is achieved using a container,Virtual Machine(VM),and Physical Machine(PM).The results of this proposed FHOEDLS confirmed a better resource capability of 0.418 and a minimized load of 0.0061.展开更多
In a cloud environment,graphics processing units(GPUs)are the primary devices used for high-performance computation.They exploit flexible resource utilization,a key advantage of cloud environments.Multiple users share...In a cloud environment,graphics processing units(GPUs)are the primary devices used for high-performance computation.They exploit flexible resource utilization,a key advantage of cloud environments.Multiple users share GPUs,which serve as coprocessors of central processing units(CPUs)and are activated only if tasks demand GPU computation.In a container environment,where resources can be shared among multiple users,GPU utilization can be increased by minimizing idle time because the tasks of many users run on a single GPU.However,unlike CPUs and memory,GPUs cannot logically multiplex their resources.Additionally,GPU memory does not support over-utilization:when it runs out,tasks will fail.Therefore,it is necessary to regulate the order of execution of concurrently running GPU tasks to avoid such task failures and to ensure equitable GPU sharing among users.In this paper,we propose a GPU task execution order management technique that controls GPU usage via time-based containers.The technique seeks to ensure equal GPU time among users in a container environment to prevent task failures.In the meantime,we use a deferred processing method to prevent GPU memory shortages when GPU tasks are executed simultaneously and to determine the execution order based on the GPU usage time.As the order of GPU tasks cannot be externally adjusted arbitrarily once the task commences,the GPU task is indirectly paused by pausing the container.In addition,as container pause/unpause status is based on the information about the available GPU memory capacity,overuse of GPU memory can be prevented at the source.As a result,the strategy can prevent task failure and the GPU tasks can be experimentally processed in appropriate order.展开更多
Container-based virtualization technology has been more widely used in edge computing environments recently due to its advantages of lighter resource occupation, faster startup capability, and better resource utilizat...Container-based virtualization technology has been more widely used in edge computing environments recently due to its advantages of lighter resource occupation, faster startup capability, and better resource utilization efficiency. To meet the diverse needs of tasks, it usually needs to instantiate multiple network functions in the form of containers interconnect various generated containers to build a Container Cluster(CC). Then CCs will be deployed on edge service nodes with relatively limited resources. However, the increasingly complex and timevarying nature of tasks brings great challenges to optimal placement of CC. This paper regards the charges for various resources occupied by providing services as revenue, the service efficiency and energy consumption as cost, thus formulates a Mixed Integer Programming(MIP) model to describe the optimal placement of CC on edge service nodes. Furthermore, an Actor-Critic based Deep Reinforcement Learning(DRL) incorporating Graph Convolutional Networks(GCN) framework named as RL-GCN is proposed to solve the optimization problem. The framework obtains an optimal placement strategy through self-learning according to the requirements and objectives of the placement of CC. Particularly, through the introduction of GCN, the features of the association relationship between multiple containers in CCs can be effectively extracted to improve the quality of placement.The experiment results show that under different scales of service nodes and task requests, the proposed method can obtain the improved system performance in terms of placement error ratio, time efficiency of solution output and cumulative system revenue compared with other representative baseline methods.展开更多
Automated guided vehicles(AGVs)are key equipment in automated container terminals(ACTs),and their operational efficiency can be impacted by conflicts and battery swapping.Additionally,AGVs have bidirectional transport...Automated guided vehicles(AGVs)are key equipment in automated container terminals(ACTs),and their operational efficiency can be impacted by conflicts and battery swapping.Additionally,AGVs have bidirectional transportation capabilities,allowing them tomove in the opposite directionwithout turning around,which helps reduce transportation time.This paper aims at the problem of AGV scheduling and bidirectional conflict-free routing with battery swapping in automated terminals.A bi-level mixed integer programming(MIP)model is proposed,taking into account task assignment,bidirectional conflict-free routing,and battery swapping.The upper model focuses on container task assignment and AGV battery swapping planning,while the lower model ensures conflict-free movement of AGVs.A double-threshold battery swapping strategy is introduced,allowing AGVs to utilize waiting time for loading for battery swapping.An improved differential evolution variable neighborhood search(IDE-VNS)algorithm is developed to solve the bi-level MIP model,aiming to minimize the completion time of all jobs.Experimental results demonstrate that compared to the differential evolution(DE)algorithm and the genetic algorithm(GA),the IDEVNS algorithmreduces fitness values by 44.49% and 45.22%,though it does increase computation time by 56.28% and 62.03%,respectively.Bidirectional transportation reduces the fitness value by an average of 10.97% when the container scale is small.As the container scale increases,the fitness value of bidirectional transportation gradually approaches that of unidirectional transportation.The results further show that the double-threshold battery swapping strategy enhances AGV utilization and reduces the fitness value.展开更多
The evolution mechanism of railway transportation network nodes driven by sea-rail intermodal transport(SRIT),a globally prevalent logistics method,has not been thoroughly investigated.From the perspective of SRIT,thi...The evolution mechanism of railway transportation network nodes driven by sea-rail intermodal transport(SRIT),a globally prevalent logistics method,has not been thoroughly investigated.From the perspective of SRIT,this study constructed a framework for understanding the evolution of railway container transport network nodes using Northeast China from 2013 to 2020 as a case study.It leverages proprietary data from 95306 Railway Freight E-commerce Platform.By employing the hybrid EWM-GA-TOPSIS model,complex network analysis,modified gravity model,and correlation and regression analyses,this study delves into the spatiotemporal patterns and dynamic transformations of railway container freight stations(RCFS).Finally,the long-term relationship between the RCFS and SRIT is explored.The results indicate that the spatial and temporal analysis of the RCFS in Northeast China from 2013 to 2020 revealed a clear polarisation trend,with the top-ranked stations mainly concentrated near ports and important transportation hubs.Additionally,the RCFS exhibited an expansionary trend;however,its development was uneven,and there was a significant increase in the number of new stations compared to abandoned stations,indicating an overall positive growth tendency.Moreover,the intensity of the SRIT at the RCFS in Northeast China notably increased.A significant positive linear relationship exists between SRIT and the freight capacity of all stations.A relatively pronounced correlation was observed for high-intensity stations,whereas a relatively weak correlation was observed for low-intensity stations.This study not only provides an effective framework for future research on RCFS within the context of SRIT but also serves as a scientific reference for promoting the implementation of the national strategy for multimodal transportation.展开更多
The population growth in Ghana has assumed an alarming rate.The provision of urban infrastructure and housing has however not been commensurate with the demand especially in housing,thus the acute housing deficit.The ...The population growth in Ghana has assumed an alarming rate.The provision of urban infrastructure and housing has however not been commensurate with the demand especially in housing,thus the acute housing deficit.The idea of using shipping containers as a building component is by no means new in the Accra Metropolis as most shipping containers are re-constructed architecturally and used for temporary accommodation needs like storage,make-shift shops,emergency shelters and site offices.The concept of using these shipping containers as modular building components in architecture however,is still foreign to building practitioners and the nation at large.This research paper set out to use the containers not for luxury apartments but to harness the merits of availability,low-cost of resource,speed of construction and structural stability of the International Standard Organization(ISO)shipping containers in addressing the housing deficiency problem in the nation by meeting the basic need of shelter.Based on the hypothesis of being a cheaper alternative to the concrete and sand-crete blocks,which is the main construction technology used now,similar house types of both technologies were compared to ascertain the variation as part of the methodology for this research.The methodology also included literature reviews and case studies.The scope of this study was limited to 2-bedroom single-storey and multi-storey house types in Accra,the capital city of Ghana.In the final analysis however,this research proved that the container house is not cheaper than the traditional blockwork and concrete construction method is and is better used in temporary accommodation,in situations where time is essential.展开更多
Structural properties of the ship container logistics network of China(SCLNC)are studied in the light of recent investigations of complex networks.SCLNC is composed of a set of routes and ports located along the sea o...Structural properties of the ship container logistics network of China(SCLNC)are studied in the light of recent investigations of complex networks.SCLNC is composed of a set of routes and ports located along the sea or river.Network properties including the degree distribution,degree correlations,clustering,shortest path length,centrality and betweenness are studied in different definition of network topology.It is found that geographical constraint plays an important role in the network topology of SCLNC.We also study the traffic flow of SCLNC based on the weighted network representation,and demonstrate the weight distribution can be described by power law or exponential function depending on the assumed definition of network topology.Other features related to SCLNC are also investigated.展开更多
Images and videos play an increasingly vital role in daily life and are widely utilized as key evidentiary sources in judicial investigations and forensic analysis.Simultaneously,advancements in image and video proces...Images and videos play an increasingly vital role in daily life and are widely utilized as key evidentiary sources in judicial investigations and forensic analysis.Simultaneously,advancements in image and video processing technologies have facilitated the widespread availability of powerful editing tools,such as Deepfakes,enabling anyone to easily create manipulated or fake visual content,which poses an enormous threat to social security and public trust.To verify the authenticity and integrity of images and videos,numerous approaches have been proposed,which are primarily based on content analysis and their effectiveness is susceptible to interference from various image or video post-processing operations.Recent research has highlighted the potential of file containers analysis as a promising forensic approach that offers efficient and interpretable results.However,there is still a lack of review articles on this kind of approach.In order to fill this gap,we present a comprehensive review of file containers-based image and video forensics in this paper.Specifically,we categorize the existing methods into two distinct stages,qualitative analysis and quantitative analysis.In addition,an overall framework is proposed to organize the exiting approaches.Then,the advantages and disadvantages of the schemes used across different forensic tasks are provided.Finally,we outline the trends in this research area,aiming to provide valuable insights and technical guidance for future research.展开更多
In the context of building a country with a strong transportation network,railway container transportation(RCT)is an important means of reducing costs,increasing efficiency,and adjusting transportation structures.Thus...In the context of building a country with a strong transportation network,railway container transportation(RCT)is an important means of reducing costs,increasing efficiency,and adjusting transportation structures.Thus,its impact on regional economic development is important.Based on data from railway container-handling stations and spatial econometric models,this study discusses the differences in the development of RCT and their impact on regional economic development at different leves.This study has three main findings:first,there are significant regional differences in the development of the RCT.The intra-regional differences between the eastern and central regions of China(which do not include Hong Kong,Macao and Taiwan)are gradually narrowing,while the regional differences in the western region are widening.Meanwhile,the intra-regional differences in important economic zones such as Pearl River Delta Economic Zone(PRDEZ),Chengdu-Chongqing Economic Zone(CYEZ),Bohai Rim Economic Zone(BHEZ),and Yangtze River Delta Economic Zone(YRDEZ)are narrowing daily.Second,the development differences of RCT in regional level and important economic regions level show different trends.The unbalanced features of large regions are increasingly evident,whereas the differences in economic regions are decreasing.However,the problem of overlapping RCT remains prominent.Third,the transformation of RCT development mode and fierce competition among transportation modes cause RCT to have a restraining effect on the regional economy at three levels.Rational allocation of resources and other means must be used to guide the transformation from inhibition to promotion,and by formulating targeted policies that will promote the development of RCT,which will improve the transportation structure and help construct a country with a strong transportation system.展开更多
A water-soluble macrocycle that bears four carboxylate anions has been designed and prepared,which forms a rectangular cavity that can efficiently encapsulate discrete electron-deficient aromatic compounds,including b...A water-soluble macrocycle that bears four carboxylate anions has been designed and prepared,which forms a rectangular cavity that can efficiently encapsulate discrete electron-deficient aromatic compounds,including berberine and palmatine.This macrocycle is revealed to be highly biocompatible and able to inhibit the bitter taste of the two drugs.展开更多
This study selected the Sino-US route data from the top 30 global container liner companies between December 1,2019,and December 29,2019,as the data source utilizing the complex network research methodology.It constru...This study selected the Sino-US route data from the top 30 global container liner companies between December 1,2019,and December 29,2019,as the data source utilizing the complex network research methodology.It constructs a Sino-US container shipping network through voyage weighting and analyzes the essential structural characteristics to explore the network’s complex structural fea-tures.The network’s evolution is examined from three perspectives,namely,time,space,and event influence,aiming to comprehens-ively explore the network’s evolution mechanism.The results revealed that:1)the weighted Sino-US container shipping network exhib-its small-world and scale-free properties.Key hub ports in the United States include NEW YORK NY,SAVANNAH GA,LOS ANGELES CA,and OAKLAND CA,whereas SHANGHAI serving as the hub port in China.The geographical distribution of these hub ports is uneven.2)Concerning the evolution of the weighted Sino-US container shipping network,from a temporal perspective,the evolution of the regional structure of the entire Sino-US region and the Inland United States is in a stage of radiative expansion and de-velopment,with a need for further enhancement in competitiveness and development speed.The evolution of the regional structure of southern China and Europe is transitioning from the stage of radiative expansion and development to an advanced equilibrium stage.The shipping development in Northern China,the Western and Eastern United States,and Asia is undergoing significant changes but faces challenges of fierce competition and imbalances.From a spatial perspective,the rationality and effectiveness of the improved weighted Barrat-Barthelemy-Vespignani(BBV)model are confirmed through theoretical derivation.The applicability of the improved evolution model is verified by simulating the evolution of the weighted Sino-US container shipping network.From an event impact per-spective,the Corona Virus Disease 2019(COVID-19)pandemic has not fundamentally affected the spatial pattern of the weighted Sino-US container shipping network but has significantly impacted the network’s connectivity.The network lacks sufficient resilience and stability in emergency situations.3)Based on the analysis of the structural characteristics and evolution of the weighted Sino-US con-tainer shipping network,recommendations for network development are proposed from three aspects:emphasizing the development of hub ports,focusing on the balanced development of the network,and optimizing the layout of Chinese ports.展开更多
Improving the cooperative scheduling efficiency of equipment is the key for automated container terminals to copewith the development trend of large-scale ships. In order to improve the solution efficiency of the exis...Improving the cooperative scheduling efficiency of equipment is the key for automated container terminals to copewith the development trend of large-scale ships. In order to improve the solution efficiency of the existing spacetimenetwork (STN) model for the cooperative scheduling problem of yard cranes (YCs) and automated guidedvehicles (AGVs) and extend its application scenarios, two improved STN models are proposed. The flow balanceconstraints in the original model are decomposed, and the trajectory constraints of YCs and AGVs are added toacquire the model STN_A. The coupling constraint in STN_A is updated, and buffer constraints are added toSTN_A so that themodel STN_B is built.As the size of the problem increases, the solution speed of CPLEX becomesthe bottleneck. So a heuristic method containing three groups of heuristic rules is designed to obtain a near-optimalsolution quickly. Experimental results showthat the computation time of STN_A is shortened by 49.47% on averageand the gap is reduced by 1.69% on average compared with the original model. The gap between the solution ofthe heuristic rules and the solution of CPLEX is less than 3.50%, and the solution time of the heuristic rules is onaverage 99.85% less than the solution time of CPLEX. Compared with STN_A, the computation time for solvingSTN_B increases by 58.93% on average.展开更多
Container ports and hinterland manufacturing are two important forces of the local participation in economic globalization.This study,taking the Pearl River Delta(PRD),China with an export-oriented economy as an examp...Container ports and hinterland manufacturing are two important forces of the local participation in economic globalization.This study,taking the Pearl River Delta(PRD),China with an export-oriented economy as an example,applies Huff and panel regres-sion models to evaluate the impact of hinterland manufacturing on the development of container ports during the period of 1993–2019.The results show that 1)the spatial patterns of hinterlands for hub ports help to determine the distribution range and scale of economic variables that affect port throughput;2)the hinterland’s gross manufacturing output has universally positive influence on port through-put,wherein export-oriented processing and the entire manufacturing industry have significantly positive impact on port throughput in 1993–2011 and 2001–2019,respectively;3)the two internal structural factors related to an export-oriented economy,labor-intensive sectors and foreign-funded terminals,have positively moderate the direct influence of hinterland manufacturing on port throughput.Our results highlight the importance of local context in understanding port-manufacturing relationship in developing economies.Based on our findings,policy implications are further proposed to enhance port network organization in PRD.展开更多
Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics system.However,the efficiency of resource scheduling significantly influences the operation pe...Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics system.However,the efficiency of resource scheduling significantly influences the operation performance of MCT.To solve the practical resource scheduling problem(RSP)in MCT efficiently,this paper has contributions to both the problem model and the algorithm design.Firstly,in the problem model,different from most of the existing studies that only consider scheduling part of the resources in MCT,we propose a unified mathematical model for formulating an integrated RSP.The new integrated RSP model allocates and schedules multiple MCT resources simultaneously by taking the total cost minimization as the objective.Secondly,in the algorithm design,a pre-selection-based ant colony system(PACS)approach is proposed based on graphic structure solution representation and a pre-selection strategy.On the one hand,as the RSP can be formulated as the shortest path problem on the directed complete graph,the graphic structure is proposed to represent the solution encoding to consider multiple constraints and multiple factors of the RSP,which effectively avoids the generation of infeasible solutions.On the other hand,the pre-selection strategy aims to reduce the computational burden of PACS and to fast obtain a higher-quality solution.To evaluate the performance of the proposed novel PACS in solving the new integrated RSP model,a set of test cases with different sizes is conducted.Experimental results and comparisons show the effectiveness and efficiency of the PACS algorithm,which can significantly outperform other state-of-the-art algorithms.展开更多
Detection and observation of reactive intermediates is an essential step in investigation of reaction pathways.However,most reactive intermediates are unstable and present at low concentrations;their short lifetimes m...Detection and observation of reactive intermediates is an essential step in investigation of reaction pathways.However,most reactive intermediates are unstable and present at low concentrations;their short lifetimes make them difficult to detect and characterize.Supramolecular containers offer opportunities for the stabilization and characterization of those labile species,through isolation from the media and protection inside the cavity of the host.In this review,we summarize the examples of labile reaction intermediates that are stabilized and characterized with the help of supramolecular containers.The container compounds include carcerands,deep cavitands and amide naphthotubes.We focus on unstable vip species-cyclobutadiene,benzocyclopropenone,o-benzyne,1,2,4,6-cycloheptatetraene,anti-Bredt's olefin,fluorophenoxycarbene,O-acylisoamide,and hemiaminalthat act as intermediates in certain organic reactions.展开更多
In this study, we delve into the realm of efficient Big Data Engineering and Extract, Transform, Load (ETL) processes within the healthcare sector, leveraging the robust foundation provided by the MIMIC-III Clinical D...In this study, we delve into the realm of efficient Big Data Engineering and Extract, Transform, Load (ETL) processes within the healthcare sector, leveraging the robust foundation provided by the MIMIC-III Clinical Database. Our investigation entails a comprehensive exploration of various methodologies aimed at enhancing the efficiency of ETL processes, with a primary emphasis on optimizing time and resource utilization. Through meticulous experimentation utilizing a representative dataset, we shed light on the advantages associated with the incorporation of PySpark and Docker containerized applications. Our research illuminates significant advancements in time efficiency, process streamlining, and resource optimization attained through the utilization of PySpark for distributed computing within Big Data Engineering workflows. Additionally, we underscore the strategic integration of Docker containers, delineating their pivotal role in augmenting scalability and reproducibility within the ETL pipeline. This paper encapsulates the pivotal insights gleaned from our experimental journey, accentuating the practical implications and benefits entailed in the adoption of PySpark and Docker. By streamlining Big Data Engineering and ETL processes in the context of clinical big data, our study contributes to the ongoing discourse on optimizing data processing efficiency in healthcare applications. The source code is available on request.展开更多
The most prominent risk assessment techniques are founded on the values of measuring and controlling the frequency and the consequences of risks in order to assure an“acceptable level”of“safeness”mainly in the lin...The most prominent risk assessment techniques are founded on the values of measuring and controlling the frequency and the consequences of risks in order to assure an“acceptable level”of“safeness”mainly in the lines of environmental,health and hygiene and port product issues.This paper examines security risk assessment approaches within the emerging role of ports.This paper contributes to the current literature by considering the ports of Greece as a case in point and by measuring the degree of its security risk orientation based on certain valid risk factors drawn from the current literature.Moreover,it presents a security risk assessment methodology into the domain of port container terminals.Their potential for ports were quantitatively and qualitatively assessed by discussing issues of security approaches within the maritime industry,in order to facilitate improvement strategies.A two-dimension empirical study was conducted,in a time range of ten years(2010-2020)in order to provide evidence regarding security risk assessment in the port container terminal of Thessaloniki,in Greece.The findings of this study have significant strategic policy implications and shed more light on the role of security risks in the overall risk orientation of container terminals in practice.Finally,further research directions in security risk in ports are proposed.展开更多
Purpose: This study aimed to enhance the prediction of container dwell time, a crucial factor for optimizing port operations, resource allocation, and supply chain efficiency. Determining an optimal learning rate for ...Purpose: This study aimed to enhance the prediction of container dwell time, a crucial factor for optimizing port operations, resource allocation, and supply chain efficiency. Determining an optimal learning rate for training Artificial Neural Networks (ANNs) has remained a challenging task due to the diverse sizes, complexity, and types of data involved. Design/Method/Approach: This research used a RandomizedSearchCV algorithm, a random search approach, to bridge this knowledge gap. The algorithm was applied to container dwell time data from the TOS system of the Port of Tema, which included 307,594 container records from 2014 to 2022. Findings: The RandomizedSearchCV method outperformed standard training methods both in terms of reducing training time and improving prediction accuracy, highlighting the significant role of the constant learning rate as a hyperparameter. Research Limitations and Implications: Although the study provides promising outcomes, the results are limited to the data extracted from the Port of Tema and may differ in other contexts. Further research is needed to generalize these findings across various port systems. Originality/Value: This research underscores the potential of RandomizedSearchCV as a valuable tool for optimizing ANN training in container dwell time prediction. It also accentuates the significance of automated learning rate selection, offering novel insights into the optimization of container dwell time prediction, with implications for improving port efficiency and supply chain operations.展开更多
基金financial support from the National Natural Science Foundation of China(Grant No.11572159).
文摘The cavity characteristics in liquid-filled containers caused by high-velocity impacts represent an important area of research in hydrodynamic ram phenomena.The dynamic expansion of the cavity induces liquid pressure variations,potentially causing catastrophic damage to the container.Current studies mainly focus on non-deforming projectiles,such as fragments,with limited exploration of shaped charge jets.In this paper,a uniquely experimental system was designed to record cavity profiles in behind-armor liquid-filled containers subjected to shaped charge jet impacts.The impact process was then numerically reproduced using the explicit simulation program ANSYS LS-DYNA with the Structured Arbitrary Lagrangian-Eulerian(S-ALE)solver.The formation mechanism,along with the dimensional and shape evolution of the cavity was investigated.Additionally,the influence of the impact kinetic energy of the jet on the cavity characteristics was analyzed.The findings reveal that the cavity profile exhibits a conical shape,primarily driven by direct jet impact and inertial effects.The expansion rates of both cavity length and maximum radius increase with jet impact kinetic energy.When the impact kinetic energy is reduced to 28.2 kJ or below,the length-to-diameter ratio of the cavity ultimately stabilizes at approximately 7.
基金supported by the National Natural Science Foundation of China(Grant Nos.12102480,52278543 and 51978660)Natural Science Foundation of Jiangsu Province(Grant No.BK20231489)。
文摘Liquid-filled containers(LFC)are widely used to store and transport petroleum,chemical reagents,and other resources.As an important target of military strikes and terrorist bombings,LFC are vulnerable to blast waves and fragments.To explore the protective effect of polyurea elastomer on LFC,the damage characteristics of polyurea coated liquid-filled container(PLFC)under the combined loading of blast shock wave and fragments were studied experimentally.The microstructure of the polyurea layer was observed by scanning electron microscopy,and the fracture and self-healing phenomena were analyzed.The simulation approach was used to explain the combined blast-and fragments-induced on the PLFC in detail.Finally,the effects of shock wave and fragment alone and in combination on the damage of PLFC were comprehensively compared.Results showed that the polyurea reduces the perforation rate of the fragment to the LFC,and the self-healing phenomenon could also reduce the liquid loss rate inside the container.The polyurea reduces the degree of depression in the center of the LFC,resulting in a decrease in the distance between adjacent fragments penetrating the LFC,and an increase in the probability of transfixion and fracture between holes.Under the close-in blast,the detonation shock wave reached the LFC before the fragment.Polyurea does not all have an enhanced effect on the protection of LFC.The presence of internal water enhances the anti-blast performance of the container,and the hydrodynamic ram(HRAM)formed by the fragment impacting the water aggravated the plastic deformation of the container.The combined action has an enhancement effect on the deformation of the LFC.The depth of the container depression was 27%higher than that of the blast shock wave alone;thus,it cannot be simply summarized as linear superposition.
文摘Virtualization is an indispensable part of the cloud for the objective of deploying different virtual servers over the same physical layer.However,the increase in the number of applications executing on the repositories results in increased overload due to the adoption of cloud services.Moreover,the migration of applications on the cloud with optimized resource allocation is a herculean task even though it is employed for minimizing the dilemma of allocating resources.In this paper,a Fire Hawk Optimization enabled Deep Learning Scheme(FHOEDLS)is proposed for minimizing the overload and optimizing the resource allocation on the hybrid cloud container architecture for migrating interoperability based applications This FHOEDLS achieves the load prediction through the utilization of deep CNN-GRU-AM model for attaining resource allocation and better migration of applications.It specifically adopted the Fire Hawk Optimization Algorithm(FHOA)for optimizing the parameters that influence the factors that aid in better interoperable application migration with improved resource allocation and minimized overhead.It considered the factors of resource capacity,transmission cost,demand,and predicted load into account during the formulation of the objective function utilized for resource allocation and application migration.The cloud simulation of this FHOEDLS is achieved using a container,Virtual Machine(VM),and Physical Machine(PM).The results of this proposed FHOEDLS confirmed a better resource capability of 0.418 and a minimized load of 0.0061.
基金supported by“Regional Innovation Strategy(RIS)”through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(MOE)(2023RIS-009).
文摘In a cloud environment,graphics processing units(GPUs)are the primary devices used for high-performance computation.They exploit flexible resource utilization,a key advantage of cloud environments.Multiple users share GPUs,which serve as coprocessors of central processing units(CPUs)and are activated only if tasks demand GPU computation.In a container environment,where resources can be shared among multiple users,GPU utilization can be increased by minimizing idle time because the tasks of many users run on a single GPU.However,unlike CPUs and memory,GPUs cannot logically multiplex their resources.Additionally,GPU memory does not support over-utilization:when it runs out,tasks will fail.Therefore,it is necessary to regulate the order of execution of concurrently running GPU tasks to avoid such task failures and to ensure equitable GPU sharing among users.In this paper,we propose a GPU task execution order management technique that controls GPU usage via time-based containers.The technique seeks to ensure equal GPU time among users in a container environment to prevent task failures.In the meantime,we use a deferred processing method to prevent GPU memory shortages when GPU tasks are executed simultaneously and to determine the execution order based on the GPU usage time.As the order of GPU tasks cannot be externally adjusted arbitrarily once the task commences,the GPU task is indirectly paused by pausing the container.In addition,as container pause/unpause status is based on the information about the available GPU memory capacity,overuse of GPU memory can be prevented at the source.As a result,the strategy can prevent task failure and the GPU tasks can be experimentally processed in appropriate order.
文摘Container-based virtualization technology has been more widely used in edge computing environments recently due to its advantages of lighter resource occupation, faster startup capability, and better resource utilization efficiency. To meet the diverse needs of tasks, it usually needs to instantiate multiple network functions in the form of containers interconnect various generated containers to build a Container Cluster(CC). Then CCs will be deployed on edge service nodes with relatively limited resources. However, the increasingly complex and timevarying nature of tasks brings great challenges to optimal placement of CC. This paper regards the charges for various resources occupied by providing services as revenue, the service efficiency and energy consumption as cost, thus formulates a Mixed Integer Programming(MIP) model to describe the optimal placement of CC on edge service nodes. Furthermore, an Actor-Critic based Deep Reinforcement Learning(DRL) incorporating Graph Convolutional Networks(GCN) framework named as RL-GCN is proposed to solve the optimization problem. The framework obtains an optimal placement strategy through self-learning according to the requirements and objectives of the placement of CC. Particularly, through the introduction of GCN, the features of the association relationship between multiple containers in CCs can be effectively extracted to improve the quality of placement.The experiment results show that under different scales of service nodes and task requests, the proposed method can obtain the improved system performance in terms of placement error ratio, time efficiency of solution output and cumulative system revenue compared with other representative baseline methods.
基金supported by National Natural Science Foundation of China(No.62073212)Shanghai Science and Technology Commission(No.23ZR1426600).
文摘Automated guided vehicles(AGVs)are key equipment in automated container terminals(ACTs),and their operational efficiency can be impacted by conflicts and battery swapping.Additionally,AGVs have bidirectional transportation capabilities,allowing them tomove in the opposite directionwithout turning around,which helps reduce transportation time.This paper aims at the problem of AGV scheduling and bidirectional conflict-free routing with battery swapping in automated terminals.A bi-level mixed integer programming(MIP)model is proposed,taking into account task assignment,bidirectional conflict-free routing,and battery swapping.The upper model focuses on container task assignment and AGV battery swapping planning,while the lower model ensures conflict-free movement of AGVs.A double-threshold battery swapping strategy is introduced,allowing AGVs to utilize waiting time for loading for battery swapping.An improved differential evolution variable neighborhood search(IDE-VNS)algorithm is developed to solve the bi-level MIP model,aiming to minimize the completion time of all jobs.Experimental results demonstrate that compared to the differential evolution(DE)algorithm and the genetic algorithm(GA),the IDEVNS algorithmreduces fitness values by 44.49% and 45.22%,though it does increase computation time by 56.28% and 62.03%,respectively.Bidirectional transportation reduces the fitness value by an average of 10.97% when the container scale is small.As the container scale increases,the fitness value of bidirectional transportation gradually approaches that of unidirectional transportation.The results further show that the double-threshold battery swapping strategy enhances AGV utilization and reduces the fitness value.
基金National Natural Science Foundation of ChinaNo.72174035+5 种基金The National Key Research and Development ProjectNo.2023YFB4302200111 Project of ChinaNo.B20082The Talent Planning in DalianNo.2022RG05。
文摘The evolution mechanism of railway transportation network nodes driven by sea-rail intermodal transport(SRIT),a globally prevalent logistics method,has not been thoroughly investigated.From the perspective of SRIT,this study constructed a framework for understanding the evolution of railway container transport network nodes using Northeast China from 2013 to 2020 as a case study.It leverages proprietary data from 95306 Railway Freight E-commerce Platform.By employing the hybrid EWM-GA-TOPSIS model,complex network analysis,modified gravity model,and correlation and regression analyses,this study delves into the spatiotemporal patterns and dynamic transformations of railway container freight stations(RCFS).Finally,the long-term relationship between the RCFS and SRIT is explored.The results indicate that the spatial and temporal analysis of the RCFS in Northeast China from 2013 to 2020 revealed a clear polarisation trend,with the top-ranked stations mainly concentrated near ports and important transportation hubs.Additionally,the RCFS exhibited an expansionary trend;however,its development was uneven,and there was a significant increase in the number of new stations compared to abandoned stations,indicating an overall positive growth tendency.Moreover,the intensity of the SRIT at the RCFS in Northeast China notably increased.A significant positive linear relationship exists between SRIT and the freight capacity of all stations.A relatively pronounced correlation was observed for high-intensity stations,whereas a relatively weak correlation was observed for low-intensity stations.This study not only provides an effective framework for future research on RCFS within the context of SRIT but also serves as a scientific reference for promoting the implementation of the national strategy for multimodal transportation.
文摘The population growth in Ghana has assumed an alarming rate.The provision of urban infrastructure and housing has however not been commensurate with the demand especially in housing,thus the acute housing deficit.The idea of using shipping containers as a building component is by no means new in the Accra Metropolis as most shipping containers are re-constructed architecturally and used for temporary accommodation needs like storage,make-shift shops,emergency shelters and site offices.The concept of using these shipping containers as modular building components in architecture however,is still foreign to building practitioners and the nation at large.This research paper set out to use the containers not for luxury apartments but to harness the merits of availability,low-cost of resource,speed of construction and structural stability of the International Standard Organization(ISO)shipping containers in addressing the housing deficiency problem in the nation by meeting the basic need of shelter.Based on the hypothesis of being a cheaper alternative to the concrete and sand-crete blocks,which is the main construction technology used now,similar house types of both technologies were compared to ascertain the variation as part of the methodology for this research.The methodology also included literature reviews and case studies.The scope of this study was limited to 2-bedroom single-storey and multi-storey house types in Accra,the capital city of Ghana.In the final analysis however,this research proved that the container house is not cheaper than the traditional blockwork and concrete construction method is and is better used in temporary accommodation,in situations where time is essential.
基金supported by Youth Foundation for Research of the Waterborne Transportation Institute.
文摘Structural properties of the ship container logistics network of China(SCLNC)are studied in the light of recent investigations of complex networks.SCLNC is composed of a set of routes and ports located along the sea or river.Network properties including the degree distribution,degree correlations,clustering,shortest path length,centrality and betweenness are studied in different definition of network topology.It is found that geographical constraint plays an important role in the network topology of SCLNC.We also study the traffic flow of SCLNC based on the weighted network representation,and demonstrate the weight distribution can be described by power law or exponential function depending on the assumed definition of network topology.Other features related to SCLNC are also investigated.
基金supported in part by Natural Science Foundation of Hubei Province of China under Grant 2023AFB016the 2022 Opening Fund for Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering under Grant 2022SDSJ02the Construction Fund for Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering under Grant 2019ZYYD007.
文摘Images and videos play an increasingly vital role in daily life and are widely utilized as key evidentiary sources in judicial investigations and forensic analysis.Simultaneously,advancements in image and video processing technologies have facilitated the widespread availability of powerful editing tools,such as Deepfakes,enabling anyone to easily create manipulated or fake visual content,which poses an enormous threat to social security and public trust.To verify the authenticity and integrity of images and videos,numerous approaches have been proposed,which are primarily based on content analysis and their effectiveness is susceptible to interference from various image or video post-processing operations.Recent research has highlighted the potential of file containers analysis as a promising forensic approach that offers efficient and interpretable results.However,there is still a lack of review articles on this kind of approach.In order to fill this gap,we present a comprehensive review of file containers-based image and video forensics in this paper.Specifically,we categorize the existing methods into two distinct stages,qualitative analysis and quantitative analysis.In addition,an overall framework is proposed to organize the exiting approaches.Then,the advantages and disadvantages of the schemes used across different forensic tasks are provided.Finally,we outline the trends in this research area,aiming to provide valuable insights and technical guidance for future research.
基金Under the auspices of National Key Research and Development Program of China(No.2023YFB4302200)National Natural Science Foundation of China(No.71831002,72174053)+1 种基金Liaoning Province Xingliao Talent Plan(No.XLYC2008030)Talent Planning in Dalian(No.2022RG05)。
文摘In the context of building a country with a strong transportation network,railway container transportation(RCT)is an important means of reducing costs,increasing efficiency,and adjusting transportation structures.Thus,its impact on regional economic development is important.Based on data from railway container-handling stations and spatial econometric models,this study discusses the differences in the development of RCT and their impact on regional economic development at different leves.This study has three main findings:first,there are significant regional differences in the development of the RCT.The intra-regional differences between the eastern and central regions of China(which do not include Hong Kong,Macao and Taiwan)are gradually narrowing,while the regional differences in the western region are widening.Meanwhile,the intra-regional differences in important economic zones such as Pearl River Delta Economic Zone(PRDEZ),Chengdu-Chongqing Economic Zone(CYEZ),Bohai Rim Economic Zone(BHEZ),and Yangtze River Delta Economic Zone(YRDEZ)are narrowing daily.Second,the development differences of RCT in regional level and important economic regions level show different trends.The unbalanced features of large regions are increasingly evident,whereas the differences in economic regions are decreasing.However,the problem of overlapping RCT remains prominent.Third,the transformation of RCT development mode and fierce competition among transportation modes cause RCT to have a restraining effect on the regional economy at three levels.Rational allocation of resources and other means must be used to guide the transformation from inhibition to promotion,and by formulating targeted policies that will promote the development of RCT,which will improve the transportation structure and help construct a country with a strong transportation system.
基金the National Natural Science Foundation of China(Nos.22271059,21921003,21890730 and 21890732)for financial support.
文摘A water-soluble macrocycle that bears four carboxylate anions has been designed and prepared,which forms a rectangular cavity that can efficiently encapsulate discrete electron-deficient aromatic compounds,including berberine and palmatine.This macrocycle is revealed to be highly biocompatible and able to inhibit the bitter taste of the two drugs.
基金Under the auspices of National Natural Science Foundation of China(No.41201473,41371975)。
文摘This study selected the Sino-US route data from the top 30 global container liner companies between December 1,2019,and December 29,2019,as the data source utilizing the complex network research methodology.It constructs a Sino-US container shipping network through voyage weighting and analyzes the essential structural characteristics to explore the network’s complex structural fea-tures.The network’s evolution is examined from three perspectives,namely,time,space,and event influence,aiming to comprehens-ively explore the network’s evolution mechanism.The results revealed that:1)the weighted Sino-US container shipping network exhib-its small-world and scale-free properties.Key hub ports in the United States include NEW YORK NY,SAVANNAH GA,LOS ANGELES CA,and OAKLAND CA,whereas SHANGHAI serving as the hub port in China.The geographical distribution of these hub ports is uneven.2)Concerning the evolution of the weighted Sino-US container shipping network,from a temporal perspective,the evolution of the regional structure of the entire Sino-US region and the Inland United States is in a stage of radiative expansion and de-velopment,with a need for further enhancement in competitiveness and development speed.The evolution of the regional structure of southern China and Europe is transitioning from the stage of radiative expansion and development to an advanced equilibrium stage.The shipping development in Northern China,the Western and Eastern United States,and Asia is undergoing significant changes but faces challenges of fierce competition and imbalances.From a spatial perspective,the rationality and effectiveness of the improved weighted Barrat-Barthelemy-Vespignani(BBV)model are confirmed through theoretical derivation.The applicability of the improved evolution model is verified by simulating the evolution of the weighted Sino-US container shipping network.From an event impact per-spective,the Corona Virus Disease 2019(COVID-19)pandemic has not fundamentally affected the spatial pattern of the weighted Sino-US container shipping network but has significantly impacted the network’s connectivity.The network lacks sufficient resilience and stability in emergency situations.3)Based on the analysis of the structural characteristics and evolution of the weighted Sino-US con-tainer shipping network,recommendations for network development are proposed from three aspects:emphasizing the development of hub ports,focusing on the balanced development of the network,and optimizing the layout of Chinese ports.
基金National Natural Science Foundation of China(62073212).
文摘Improving the cooperative scheduling efficiency of equipment is the key for automated container terminals to copewith the development trend of large-scale ships. In order to improve the solution efficiency of the existing spacetimenetwork (STN) model for the cooperative scheduling problem of yard cranes (YCs) and automated guidedvehicles (AGVs) and extend its application scenarios, two improved STN models are proposed. The flow balanceconstraints in the original model are decomposed, and the trajectory constraints of YCs and AGVs are added toacquire the model STN_A. The coupling constraint in STN_A is updated, and buffer constraints are added toSTN_A so that themodel STN_B is built.As the size of the problem increases, the solution speed of CPLEX becomesthe bottleneck. So a heuristic method containing three groups of heuristic rules is designed to obtain a near-optimalsolution quickly. Experimental results showthat the computation time of STN_A is shortened by 49.47% on averageand the gap is reduced by 1.69% on average compared with the original model. The gap between the solution ofthe heuristic rules and the solution of CPLEX is less than 3.50%, and the solution time of the heuristic rules is onaverage 99.85% less than the solution time of CPLEX. Compared with STN_A, the computation time for solvingSTN_B increases by 58.93% on average.
基金Under the auspices of the National Natural Science Foundation of China(No.41930646)Guangdong Natural Science Foundation(No.2022A1515011572)。
文摘Container ports and hinterland manufacturing are two important forces of the local participation in economic globalization.This study,taking the Pearl River Delta(PRD),China with an export-oriented economy as an example,applies Huff and panel regres-sion models to evaluate the impact of hinterland manufacturing on the development of container ports during the period of 1993–2019.The results show that 1)the spatial patterns of hinterlands for hub ports help to determine the distribution range and scale of economic variables that affect port throughput;2)the hinterland’s gross manufacturing output has universally positive influence on port through-put,wherein export-oriented processing and the entire manufacturing industry have significantly positive impact on port throughput in 1993–2011 and 2001–2019,respectively;3)the two internal structural factors related to an export-oriented economy,labor-intensive sectors and foreign-funded terminals,have positively moderate the direct influence of hinterland manufacturing on port throughput.Our results highlight the importance of local context in understanding port-manufacturing relationship in developing economies.Based on our findings,policy implications are further proposed to enhance port network organization in PRD.
基金This research was supported in part by the National Key Research and Development Program of China under Grant 2022YFB3305303in part by the National Natural Science Foundations of China(NSFC)under Grant 62106055+1 种基金in part by the Guangdong Natural Science Foundation under Grant 2022A1515011825in part by the Guangzhou Science and Technology Planning Project under Grants 2023A04J0388 and 2023A03J0662.
文摘Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics system.However,the efficiency of resource scheduling significantly influences the operation performance of MCT.To solve the practical resource scheduling problem(RSP)in MCT efficiently,this paper has contributions to both the problem model and the algorithm design.Firstly,in the problem model,different from most of the existing studies that only consider scheduling part of the resources in MCT,we propose a unified mathematical model for formulating an integrated RSP.The new integrated RSP model allocates and schedules multiple MCT resources simultaneously by taking the total cost minimization as the objective.Secondly,in the algorithm design,a pre-selection-based ant colony system(PACS)approach is proposed based on graphic structure solution representation and a pre-selection strategy.On the one hand,as the RSP can be formulated as the shortest path problem on the directed complete graph,the graphic structure is proposed to represent the solution encoding to consider multiple constraints and multiple factors of the RSP,which effectively avoids the generation of infeasible solutions.On the other hand,the pre-selection strategy aims to reduce the computational burden of PACS and to fast obtain a higher-quality solution.To evaluate the performance of the proposed novel PACS in solving the new integrated RSP model,a set of test cases with different sizes is conducted.Experimental results and comparisons show the effectiveness and efficiency of the PACS algorithm,which can significantly outperform other state-of-the-art algorithms.
基金supported by the National Natural Science Foundation of China(Nos.22071144 and 22101169)Shanghai Scientific and Technological Committee(No.22010500300)。
文摘Detection and observation of reactive intermediates is an essential step in investigation of reaction pathways.However,most reactive intermediates are unstable and present at low concentrations;their short lifetimes make them difficult to detect and characterize.Supramolecular containers offer opportunities for the stabilization and characterization of those labile species,through isolation from the media and protection inside the cavity of the host.In this review,we summarize the examples of labile reaction intermediates that are stabilized and characterized with the help of supramolecular containers.The container compounds include carcerands,deep cavitands and amide naphthotubes.We focus on unstable vip species-cyclobutadiene,benzocyclopropenone,o-benzyne,1,2,4,6-cycloheptatetraene,anti-Bredt's olefin,fluorophenoxycarbene,O-acylisoamide,and hemiaminalthat act as intermediates in certain organic reactions.
文摘In this study, we delve into the realm of efficient Big Data Engineering and Extract, Transform, Load (ETL) processes within the healthcare sector, leveraging the robust foundation provided by the MIMIC-III Clinical Database. Our investigation entails a comprehensive exploration of various methodologies aimed at enhancing the efficiency of ETL processes, with a primary emphasis on optimizing time and resource utilization. Through meticulous experimentation utilizing a representative dataset, we shed light on the advantages associated with the incorporation of PySpark and Docker containerized applications. Our research illuminates significant advancements in time efficiency, process streamlining, and resource optimization attained through the utilization of PySpark for distributed computing within Big Data Engineering workflows. Additionally, we underscore the strategic integration of Docker containers, delineating their pivotal role in augmenting scalability and reproducibility within the ETL pipeline. This paper encapsulates the pivotal insights gleaned from our experimental journey, accentuating the practical implications and benefits entailed in the adoption of PySpark and Docker. By streamlining Big Data Engineering and ETL processes in the context of clinical big data, our study contributes to the ongoing discourse on optimizing data processing efficiency in healthcare applications. The source code is available on request.
文摘The most prominent risk assessment techniques are founded on the values of measuring and controlling the frequency and the consequences of risks in order to assure an“acceptable level”of“safeness”mainly in the lines of environmental,health and hygiene and port product issues.This paper examines security risk assessment approaches within the emerging role of ports.This paper contributes to the current literature by considering the ports of Greece as a case in point and by measuring the degree of its security risk orientation based on certain valid risk factors drawn from the current literature.Moreover,it presents a security risk assessment methodology into the domain of port container terminals.Their potential for ports were quantitatively and qualitatively assessed by discussing issues of security approaches within the maritime industry,in order to facilitate improvement strategies.A two-dimension empirical study was conducted,in a time range of ten years(2010-2020)in order to provide evidence regarding security risk assessment in the port container terminal of Thessaloniki,in Greece.The findings of this study have significant strategic policy implications and shed more light on the role of security risks in the overall risk orientation of container terminals in practice.Finally,further research directions in security risk in ports are proposed.
文摘Purpose: This study aimed to enhance the prediction of container dwell time, a crucial factor for optimizing port operations, resource allocation, and supply chain efficiency. Determining an optimal learning rate for training Artificial Neural Networks (ANNs) has remained a challenging task due to the diverse sizes, complexity, and types of data involved. Design/Method/Approach: This research used a RandomizedSearchCV algorithm, a random search approach, to bridge this knowledge gap. The algorithm was applied to container dwell time data from the TOS system of the Port of Tema, which included 307,594 container records from 2014 to 2022. Findings: The RandomizedSearchCV method outperformed standard training methods both in terms of reducing training time and improving prediction accuracy, highlighting the significant role of the constant learning rate as a hyperparameter. Research Limitations and Implications: Although the study provides promising outcomes, the results are limited to the data extracted from the Port of Tema and may differ in other contexts. Further research is needed to generalize these findings across various port systems. Originality/Value: This research underscores the potential of RandomizedSearchCV as a valuable tool for optimizing ANN training in container dwell time prediction. It also accentuates the significance of automated learning rate selection, offering novel insights into the optimization of container dwell time prediction, with implications for improving port efficiency and supply chain operations.
