Maritime traffic service networks and information systems play a vital role in maritime traffic safety management. The data collected from the maritime traffic networks are essential for the ...perception of traffic dynamics and predictive traffic regulation. This paper is devoted to surveying the key processing components in maritime traffic networks. Specifically, the latest progress on maritime traffic data mining technologies for maritime traffic pattern extraction and the recent effort on vessels' motion forecasting for better situation awareness are reviewed. Through the review, we highlight that the traffic pattern knowledge presents valued insights for wide-spectrum domain application purposes, and serves as a prerequisite for the knowledge based forecasting techniques that are growing in popularity. The development of maritime traffic research in pattern mining and traffic forecasting reviewed in this paper affirms the importance of advanced maritime traffic studies and the great potential in maritime traffic safety and intelligence enhancement to accommodate the implementation of the Internet of Things, artificial intelligence technologies, and knowledge engineering and big data computing solution.
Maritime traffic prediction is critical for ocean transportation safety management. In this paper, we propose a novel knowledge assisted methodology for maritime traffic forecasting based on a ...vessel's waterway pattern and motion behavior. The vessel's waterway pattern is extracted through a proposed lattice-based DBSCAN algorithm that significantly reduces the problem scale, and its motion behavior is quantitatively modeled for the first time using kernel density estimation. The proposed methodology facilitates the knowledge extraction, storage, and retrieval, allowing for seamless knowledge transfer to support maritime traffic forecasting. By incorporating both the vessel's waterway pattern and motion behavior knowledge, our solution suggests a set of probable coordinates with the corresponding probability as the forecasting output. The proposed forecasting algorithm is capable of accurately predicting maritime traffic 5, 30, and 60 min ahead, while its computation can be efficiently completed in milliseconds for single vessel prediction. Owing to such a high computational efficiency, an extensive predictive analysis of hundreds of vessels has been reported for the first time in this paper. A web-based prototype platform is implemented for Singapore waters to demonstrate the solution's feasibility in a real-world maritime operation system. The proposed approaches can be generalized for other marine waters around the world.
Inconsistent conclusions in past studies on the association between poor glycaemic control and the risk of hospitalization for heart failure (HHF) have been reported largely due to the analysis of ...non-trajectory-based HbA1c values. Trajectory analysis can incorporate the effects of HbA1c variability across time, which may better elucidate its association with macrovascular complications. Furthermore, studies analysing the relationship between HbA1c trajectories from diabetes diagnosis and the occurrence of HHF are scarce.
This is a prospective cohort study of the SingHealth Diabetes Registry (SDR). 17,389 patients diagnosed with type 2 diabetes mellitus (T2DM) from 2013 to 2016 with clinical records extending to the end of 2019 were included in the latent class growth analysis to extract longitudinal HbA1c trajectories. Association between HbA1c trajectories and risk of first known HHF is quantified with the Cox Proportional Hazards (PH) model.
5 distinct HbA1c trajectories were identified as 1. low stable (36.1%), 2. elevated stable (40.4%), 3. high decreasing (3.5%), 4. high with a sharp decline (10.8%), and 5. moderate decreasing (9.2%) over the study period of 7 years. Poorly controlled HbA1c trajectories (Classes 3, 4, and 5) are associated with a higher risk of HHF. Using the diabetes diagnosis time instead of a commonly used pre-defined study start time or time from recruitment has an impact on HbA1c clustering results.
Findings suggest that tracking the evolution of HbA1c with time has its importance in assessing the HHF risk of T2DM patients, and T2DM diagnosis time as a baseline is strongly recommended in HbA1c trajectory modelling. To the authors' knowledge, this is the first study to identify an association between HbA1c trajectories and HHF occurrence from diabetes diagnosis time.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The structure and properties of public transportation networks have great implications for urban planning, public policies and infectious disease control. We contribute a complex weighted network ...analysis of travel routes on the Singapore rail and bus transportation systems. We study the two networks using both topological and dynamical analyses. Our results provide additional evidence that a dynamical study adds to the information gained by traditional topological analysis, providing a richer view of complex weighted networks. For example, while initial topological measures showed that the rail network is almost fully connected, dynamical measures highlighted hub nodes that experience disproportionately large traffic. The dynamical assortativity of the bus networks also differed from its topological counterpart. In addition, inspection of the weighted eigenvector centralities highlighted a significant difference in traffic flows for both networks during weekdays and weekends, suggesting the importance of adding a temporal perspective missing from many previous studies.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
An index for real-time collision risk assessment is the basis for the safe navigation of ships. To consider dimension related factors more accurately and objectively in the collision risk index, and ...to enhance the readability of the index in collision avoidance decision-making, we propose a novel index by combining the dimension data from automatic identification system (AIS) and velocity obstacle approach, namely the ‘margin of projected collision (MPC)’ index. Compared with traditional existing indicators, our proposed index can more accurately and objectively judge whether the two ships collide if the current state of motion is maintained. Also, the numerical meaning of quantified risk is innovatively directional in the state of motion (i.e., course and speed), so the proposed index may additionally provide navigation assistance information including proactive warnings for dangerous behaviour and behaviour references for collision avoidance. In addition, through the real encounter cases with high collision risk, we demonstrate that our proposed index has high practical value and can be used as a good supplement to the traditional collision risk index, especially in high-precision applications such as waters with heavy maritime traffic and maritime autonomous surface ships (MASSs).
•Proposes a novel index for ship collision assessment- ‘margin of projected collision (MPC)’ index.•Introduce the method of judging whether two ships collide based on the dimension data from AIS and Velocity Obstacle.•Additional proactive warning can be provided by proposed index for dangerous ship maneuvering behaviour.•Reference information of ship maneuvering behaviour can be provided by proposed index for collision avoidance.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In the field of maritime safety, ship encounters are a core component of traffic management and analysis. The calculation of the closest point of approach (CPA) is one of the most important methods ...for collision risk assessment during an encounter. Due to the factors influencing collision risk in water transportation, the existing CPA index exhibits uncertainties in the awareness of dangerous situations. In this paper, to overcome the shortcoming of the CPA index, which does not consider the vessel dimension, we utilize a polygon to represent the ship position based on related information from automatic identification system (AIS) and propose a method to obtain corrected values of the distance at the CPA (DCPA) and time to the CPA (TCPA) through the geometric relationship of the relative motion between involved vessels. Case analysis is conducted through practical encounter cases in a traffic-intensive area outside a port. The comparison results verify that the proposed method effectively reduces the uncertainties of the original point-based CPA index to better assess the collision risk. The advantage of our correction method is that the dimension-related influencing factors can be integrated without manual intervention, and the improved index retains the objectivity and clear physical meaning of the original CPA index. Therefore, the proposed method has high practical value, especially in busy water areas where a high-risk assessment accuracy is required.
Weather factors are widely studied for their effects on indicating dengue incidence trends. However, these studies have been limited due to the complex epidemiology of dengue, which involves dynamic ...interplay of multiple factors such as herd immunity within a population, distinct serotypes of the virus, environmental factors and intervention programs. In this study, we investigate the impact of weather factors on dengue in Singapore, considering the disease epidemiology and profile of virus serotypes. A Poisson regression combined with Distributed Lag Non-linear Model (DLNM) was used to evaluate and compare the impact of weekly Absolute Humidity (AH) and other weather factors (mean temperature, minimum temperature, maximum temperature, rainfall, relative humidity and wind speed) on dengue incidence from 2001 to 2009. The same analysis was also performed on three sub-periods, defined by predominant circulating serotypes. The performance of DLNM regression models were then evaluated through the Akaike's Information Criterion. From the correlation and DLNM regression modeling analyses of the studied period, AH was found to be a better predictor for modeling dengue incidence than the other unique weather variables. Whilst mean temperature (MeanT) also showed significant correlation with dengue incidence, the relationship between AH or MeanT and dengue incidence, however, varied in the three sub-periods. Our results showed that AH had a more stable impact on dengue incidence than temperature when virological factors were taken into consideration. AH appeared to be the most consistent factor in modeling dengue incidence in Singapore. Considering the changes in dominant serotypes, the improvements in vector control programs and the inconsistent weather patterns observed in the sub-periods, the impact of weather on dengue is modulated by these other factors. Future studies on the impact of climate change on dengue need to take all the other contributing factors into consideration in order to make meaningful public policy recommendations.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This study explores the association between the duration and variation of infant sleep trajectories and subsequent cognitive school readiness at 48-50 months.
Participants were 288 multi-ethnic ...children, within the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort. Caregiver-reported total, night and day sleep durations were obtained at 3, 6, 9, 12, 18, 24 using the Brief Infant Sleep Questionnaire and 54 months using the Child Sleep Habits Questionnaire. Total, night and day sleep trajectories with varying durations (short, moderate, or long) and variability (consistent or variable; defined by standard errors) were identified. The cognitive school readiness test battery was administered when the children were between 48 and 50 months old. Both unadjusted adjusted analysis of variance models and adjusted analysis of covariance models (for confounders) were performed to assess associations between sleep trajectories and individual school readiness tests in the domains of language, numeracy, general cognition and memory.
In the unadjusted models, children with short variable total sleep trajectories had poorer performance on language tests compared to those with longer and more consistent trajectories. In both unadjusted and adjusted models, children with short variable night sleep trajectories had poorer numeracy knowledge compared to their counterparts with long consistent night sleep trajectories. There were no equivalent associations between sleep trajectories and school readiness performance for tests in the general cognition or memory domains. There were no significant findings for day sleep trajectories.
Findings suggest that individual differences in longitudinal sleep duration patterns from as early as 3 months of age may be associated with language and numeracy aspects of school readiness at 48-50 months of age. This is important, as early school readiness, particularly the domains of language and mathematics, is a key predictor of subsequent academic achievement.
Abstract
Dengue, a mosquito-transmitted viral disease, has posed a public health challenge to Singaporean residents over the years. In 2020, Singapore experienced an unprecedented dengue outbreak. We ...collected a dataset of geographical dengue clusters reported by the National Environment Agency (NEA) from 15 February to 9 July in 2020, covering the nationwide lockdown associated with
Covid
-19 during the period from 7 April to 1 June. NEA regularly updates the dengue clusters during which an infected person may be tagged to one cluster based on the most probable infection location (residential apartment or workplace address), which is further matched to fine-grained spatial units with an average coverage of about 1.35 km
2
. Such dengue cluster dataset helps not only reveal the dengue transmission patterns, but also reflect the effects of lockdown on dengue spreading dynamics. The resulting data records are released in simple formats for easy access to facilitate studies on dengue epidemics.
The topology of a supply chain network affects the impacts of disruptions in it. We formulate a network-based measure of the impact of a disruption loss in a supply chain propagating downstream from ...an originating node. The measure takes into account the loss profile of the originating node, the structure of the supply network, and the resilience of the network components. We obtain an analytical expression for the impact measure under a beta-distributed initial loss (generalizable to any continuous distribution supported on the interval 0,1), under a breakthrough scenario (in which a fraction of the initial production loss reaches a focal company downstream as opposed to containment upstream or at the originating point). Furthermore, we obtain a closed-form solution for a supply chain network with a k-ary tree topology; a numerical study is performed for a scale-free network and a random network. Our proposed approach enables the evaluation of potential losses for a focal company considering its supply chain network structure, which may help the company to plan or redesign a robust and resilient network in response to different types of disruptions.
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