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Archived seismograms recorded in the 20th century present a valuable source of information for monitoring earthquake activity. However, old data, which are only available as scanned paper-based images should be digitised and converted from raster to vector format prior to reuse for geophysical modelling. Seismograms have special characteristics and specific featuresrecorded by a seismometer and encrypted in the images: signal trace lines, minute time gaps, timing and wave amplitudes. This information should be recognised and interpreted automatically when processing archives of seismograms containing large collections of data. The objective was to automatically digitise historical seismograms obtained from the archives of the Royal Observatory of Belgium (ROB). The images were originallyrecorded by the Galitzine seismometer in 1954 in Uccle seismic station, Belgium. A dataset included 145 TIFF images which required automatic approach of data processing. Software for digitising seismograms are limited and many have disadvantages. We applied the DigitSeis for machine-based vectorisation and reported here a full workflowof data processing. This included pattern recognition, classification, digitising, corrections and converting TIFFs to the digital vector format. The generated contours of signals were presented as time series and converted into digital format (mat files) which indicated information on ground motion signals contained in analog seismograms. We performed the quality control of the digitised traces in Python to evaluate the discriminating functionality of seismic signals by DigitSeis. We shown a robust approach of DigitSeis as a powerful toolset for processing analog seismic signals. The graphical visualisation of signal traces and analysis of the performed vectorisation results shown that the algorithms of data processing performed accurately and can be recommended in similar applications of seismic signal processing in future related works in geophysical research.

Under the background of Energy Internet, the ever-growing scale of the electric power system has brought new challenges and opportunities. Numerous categories of measurement data, as the cornerstone of communication, play a crucial role in the security and stability of the system. However, the present sampling and transmission equipment inevitably suffers from data missing, which seriously degrades the stable operation and state estimation. Therefore, in this paper, we consider the load data as an example and first develop a missing detection algorithm in terms of the absolute difference sequence (ADS) and linear correlation to detect any potential missing data. Then, based on the detected results, we put forward a missing recovery model named cascaded convolutional autoencoders (CCAE), to recover those missing data. Innovatively, a special preprocessing method has been adopted to reshape the one-dimensional load data as a two-dimensional matrix, and hence, the image inpainting technologies can be conducted to address the problem. Also, CCAE is designed to reconstruct the missing data grade by grade due to its priority strategy, which enhances the robustness upon extreme missing situations. The numerical results on the load data of the Belgium grid validate the promising performance and effectiveness of the proposed solutions. [ABSTRACT FROM AUTHOR]

The materials balance condition is a fundamental adding up condition, which essentially says that: “what goes in must come out”. In this paper we argue that a number of the recently developed methods of incorporating pollution measures into standard productive efficiency models may be inconsistent with this fundamental condition. We propose an alternative method that involves the incorporation of the materials balance concept into the production model in a similar manner to which price information is normally incorporated. This produces a new environmental efficiency measure that can be decomposed into technical and allocative components, in a similar manner to the conventional cost efficiency decomposition. The approach is illustrated with the case of phosphorus emission on Belgian pig-finishing farms, using data envelopment analysis (DEA) methods. Our results indicate that a substantial proportion of nutrient pollution on these farms can be abated in a cost reducing manner. [ABSTRACT FROM AUTHOR]

This paper deals with symmetrical data that can be modelled based on Gaussian distribution, such as linear mixed models for longitudinal data. The latent factor linear mixed model (LFLMM) is a method generally used for analysing changes in high-dimensional longitudinal data. It is usual that the model estimates are based on the expectation-maximization (EM) algorithm, but unfortunately, the algorithm does not produce the standard errors of the regression coefficients, which then hampers testing procedures. To fill in the gap, the Supplemented EM (SEM) algorithm for the case of fixed variables is proposed in this paper. The computational aspects of the SEM algorithm have been investigated by means of simulation. We also calculate the variance matrix of beta using the second moment as a benchmark to compare with the asymptotic variance matrix of beta of SEM. Both the second moment and SEM produce symmetrical results, the variance estimates of beta are getting smaller when number of subjects in the simulation increases. In addition, the practical usefulness of this work was illustrated using real data on political attitudes and behaviour in Flanders-Belgium. [ABSTRACT FROM AUTHOR]

Cone penetration testing (CPT) is one of the most efficient and versatile methods currently available for geotechnical, lithostratigraphic and hydrogeological site characterization. Currently available methods for soil behaviour type classification (SBT) of CPT data however have severe limitations, often restricting their application to a local scale. For parameterization of regional groundwater flow or geotechnical models, and delineation of regional hydro- or lithostratigraphy, regional SBT classification would be very useful. This paper investigates the use of model-based clustering for SBT classification, and the influence of different clustering approaches on the properties and spatial distribution of the obtained soil classes. We additionally propose a methodology for automated lithostratigraphic mapping of regionally occurring sedimentary units using SBT classification. The methodology is applied to a large CPT dataset, covering a groundwater basin of ~60 km2 with predominantly unconsolidated sandy sediments in northern Belgium. Results show that the model-based approach is superior in detecting the true lithological classes when compared to more frequently applied unsupervised classification approaches or literature classification diagrams. We demonstrate that automated mapping of lithostratigraphic units using advanced SBT classification techniques can provide a large gain in efficiency, compared to more time-consuming manual approaches and yields at least equally accurate results. [ABSTRACT FROM AUTHOR]

Explicit criteria, such as the STOPP/START criteria, are increasingly used both in clinical practice and in research to identify potentially inappropriate prescribing in older people. In an article on the STOPP/START criteria version 2, O'Mahony et al. have pointed out the advantages of developing computerised criteria. Both clinical decision support systems to support healthcare professionals and software applications to automatically detect inappropriate prescribing in research studies can be developed. In the process of developing such tools, difficulties may occur. In the context of a research study, we have developed an algorithm to automatically apply STOPP/START criteria version 2 to our research database. We comment in this paper on different kinds of difficulties encountered and make suggestions that could be taken into account when developing the next version of the criteria. [ABSTRACT FROM AUTHOR]

SUMMARY In this paper, we propose an optimal bidding strategy for industrial combined heat and power (CHP) installations selling their power on multiple markets. This corresponds to the typical situation where power is traded on a day-ahead market (DAM) and a continuous intraday market (CIM). Each market has its own trading rules. The considered installations consist of a CHP, a conventional heating installation and a heat buffer. Each device has its own constraints, such as maximum and minimum deliverable heat and electrical power, and minimum and maximum buffer capacity. The objective is to determine the bidding strategy that will maximise the expected profit, while the future time evolution of both heat demand and market prices are unknown. To tackle this problem, we assume that the probability density functions (PDFs) of these variables are known or can be extracted from historical data. Then, by applying a tailored stochastic programming algorithm, the optimal bidding strategy can be constructed based on these PDFs and includes the different market rules and constraints on the installation. For a DAM, the bidding functions must be estimated in advance, which is a typical open-loop problem. On the other hand, the bidding functions for a CIM may be estimated almost in real time. This new scheme is exemplified for the Belgian market. Combining both markets can increase the expected profits significantly because risks due to uncertainties in heat demand are better controlled. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The Intensive Care Unit (ICU) is an extremely data-intensive environment where each patient needs to be monitored 24/7. Bedside monitors continuously register vital patient values (such as serum creatinine, systolic blood pressure) which are recorded frequently in the hospital database (e.g. every 2 min in the ICU of the Ghent University Hospital), laboratories generate hundreds of results of blood and urine samples, and nurses measure blood pressure and temperature up to 4 times an hour. The processing of such large amount of data requires an automated system to support the physicians' daily work. The Intensive Care Service Platform (ICSP) offers the needed support through the development of medical support services for processing and monitoring patients' data. With an increased deployment of these medical support services, reusing existing services as building blocks to create new services offers flexibility to the developer and accelerates the design process. This paper presents a new addition to the ICSP, the Dynamic Composer for Web services. Based on a semantic description of the medical support services, this Composer enables a service to be executed by creating a composition of medical services that provide the needed calculations. The composition is achieved using various algorithms satisfying certain quality of service (QoS) constraints and requirements. In addition to the automatic composition the paper also proposes a recovery mechanism in case of unavailable services. When executing the composition of medical services, unavailable services are dynamically replaced by equivalent services or a new composition achieving the same result. The presented platform and QoS algorithms are put through extensive performance and scalability tests for typical ICU scenarios, in which basic medical services are composed to a complex patient monitoring service., (Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.)

The importance of computer aided decision making is continuously increasing. In the ICU, medical decision support services gather and process medical data of patients and present results and suggestions to the medical staff. The medical decision support services can monitor for example blood pressure, creatinine levels or the usage of antibiotics. If certain levels are crossed, they raise alerts so that the medical staff can take appropriate actions if required. This significantly reduces the amount of data needing to be processed by the medical staff. To handle the large amount of data that is generated by the ICU on a daily basis, a platform for routing and processing this data is necessary. In this paper we propose a platform based on JAIN SLEE and an Enterprise Service Bus. The platform takes care of the routing of the data to the appropriate services and allows to easily deploy and manage services. In this paper, we present the design details and the evaluation results. Furthermore, it is shown that the platform is capable of routing and processing all the events generated by the ICU within strict time constraints.

The paper investigates the geometric calibration of a rotating gamma camera for pinhole (PH) single photon emission computed tomography (SPECT) imaging. Most calibration methods previously applied in PH-SPECT assume that the motion of the camera around the object belongs to a well-defined class described by a small number of geometric parameters, for instance seven parameters for a circular acquisition with a single pinhole camera. The proposed new method refines an initial parametric calibration by applying to each position of the camera a rigid body transformation that is determined to improve the fit between the measured and calculated projections of the calibration sources. A stable estimate of this transformation can be obtained with only three calibration sources by linearizing the equations around the position estimated by the initial parametric calibration. The performance of the method is illustrated using simulated and measured micro-SPECT data.

This paper evaluates the performance of an algorithm developed for opportunistic, selective screening of women for chlamydial infection in general practice in Antwerp, Belgium. Its performance was examined in 2 independent sets of patients: A) a cohort of 326 women participating in a pilot screening study, and B) a sample of 25 Chlamydia positive women, identified from the records of a laboratory of clinical microbiology. For group A, positive and negative predictive values were calculated and the accuracy of the algorithm was assessed. For group B, we examined the proportion of patients complying with the algorithm. In group A, the screening algorithm would have detected 73% of the cases in 35.6% of the population. The positive and negative predictive values were 7.7% and 98.4%, respectively. In group B, 84% of patients complied with the algorithm. The screening algorithm worked reasonably well in 2 datasets from a similar population studied 2 y later, but needs further validation.

The catchment averaged actual evapotranspiration rate is a hydrologic model variable that is difficult to quantify. Evapotranspiration rates -- up till present -- cannot be continuously observed at the catchment scale. The objective of this paper is to estimate the evapotranspiration rates (or its energy equivalent, the latent heat fluxes LE) for a heterogeneous catchment of 102.3 km² in Belgium using three fundamentally different algorithms. One possible manner to observe this variable could be the continuous measurement of sensible heat fluxes (H) across large distances (in the order of kilometers) using a large aperture scintillometer (LAS), and converting these observations into evapotranspiration rates. Latent heat fluxes are obtained through the energy balance equation using a series of sensible heat fluxes measured with a LAS over a distance of 9.5 km in the catchment, and point measurements of net radiation (Rn) and ground heat flux (G) upscaled to catchment average through the use of TOPLATS, a physically based land surface model. The resulting LE-values are then compared to results from the remote sensing based surface energy balance algorithm ETLook and the land surface model. Firstly, the performance of ETLook for the energy balance terms has been assessed at the point scale and at the catchment scale. Secondly, consistency between daily evapotranspiration rates from ETLook, TOPLATS and LAS is shown. [ABSTRACT FROM AUTHOR]

Spatial interpolation of precipitation data is of great importance for hydrological modelling. Geostatistical methods (kriging) are widely applied in spatial interpolation from point measurement to continuous surfaces. The first step in kriging computation is the semi-variogram modelling which usually used only one variogram model for all-moment data. The objective of this paper was to develop different algorithms of spatial interpolation for daily rainfall on 1 km² regular grids in the catchment area and to compare the results of geostatistical and deterministic approaches. This study leaned on 30-yr daily rainfall data of 70 raingages in the hilly landscape of the Ourthe and Ambleve catchments in Belgium (2908 km²). This area lies between 35 and 693m in elevation and consists of river net- works, which are tributaries of the Meuse River. For geostatistical algorithms, seven semi-variogram models (logarithmic, power, exponential, Gaussian, rational quadratic, spherical and penta-spherical) were fitted to daily sample semi-variogram on a daily basis. These seven variogram models were also adopted to avoid negative interpolated rainfall. The elevation, extracted from a digital elevation model, was incorporated into multivariate geostatistics. Seven validation raingages and cross validation were used to compare the interpolation performance of these algorithms applied to different densities of raingages. We found that between the seven variogram models used, the Gaussian model was the most frequently best fit. Using seven variogram models can avoid negative daily rainfall in ordinary kriging. The negative estimates of kriging were observed for convective more than stratiform rain. The performance of the different methods varied slightly according to the density of raingages, particularly between 8 and 70 raingages but it was much different for interpolation using 4 raingages. Spatial interpolation with the geostatistical and Inverse Distance Weighting (IDW) algorithms outperformed considerably the interpolation with the Thiessen polygon, commonly used in various hydrological models. Integrating elevation into Kriging with an External Drift (KED) and Ordinary Cokriging (OCK) did not improve the interpolation accuracy for daily rainfall. Ordinary Kriging (ORK) and IDWwere considered to be the best methods, as they provided smallest RMSE value for nearly all cases. Care should be taken in applying UNK and KED when interpolating daily rainfall with very few neighbourhood sample points. These recommendations complement the results reported in the literature. ORK, UNK and KED using only spherical model offered a slightly better result whereas OCK using seven variogram models achieved better result. [ABSTRACT FROM AUTHOR]

The vehicle-routing problem (VRP) has many variants, including the most accurate models of real-life transportation tasks, making it one of the most important mathematical problems in the field of logistics. Our goal was to design an algorithm that can race against the most recent solutions for VRP and capacitated VRP (CVRP), while also being applicable to real-life models with simulations of real transports. Our algorithm is a variant of the bacterial memetic algorithm (BMA), which we improve upon with novel operators and better methods for manual parameter optimization. The key to our performance is a balanced mixture of the global search of evolutionary algorithms, local search of 2-OPT variants, and the pseudo-global search of probabilistic construction algorithms. Our algorithm benefits from the advantages of all three methods resulting in fast convergence and avoidance of global minima. This is the first time BMA is applied for VRP, meaning that we had to adapt the method for the new problem. We compare our method with some of the most-used methods for VRP on the ABEFMP 1995 dataset. We provide comparison results with the coronavirus herd immunity optimizer, genetic algorithm, hybridization of genetic algorithm with neighborhood search, firefly algorithm, enhanced firefly algorithm, ant colony optimization, and variable neighborhood search. Our algorithm performed better on all data instances, yielding at least a 30 % improvement. We present our best result on the Belgium 2017 dataset for future reference. Finally, we show that our algorithm is capable of handling real-life models. Here we are also illustrating the significance of the different parameters. [ABSTRACT FROM AUTHOR]

Background and aims: Phosphatidylethanol 16:0/18:1 (PEth) is a biomarker for alcohol intake. It has a half‐life of 7.9 days. Chronic alcohol consumption causes high PEth values. It can take weeks before PEth values fall below the decision limit for 'alcohol abstinence'. Our aim was to validate whether alcohol abstinence can be determined based on two consecutive PEth results above the decision limit. Design Observational study. Setting: Belgium, February 2019. The study was linked to a social initiative in Belgium, 'Tournée Minérale'. Participants: Adults (aged > 18 years, n = 796) with varying drinking habits who self‐reportedly refrained from alcohol consumption during the study. Measurements A validated liquid chromatography–tandem mass spectrometry method was used to quantify PEth in participants' dried blood samples, collected at three time‐points via remote fingerprick‐based self‐sampling. Findings A population‐based algorithm to evaluate abstinence based on 95% prediction limits was developed by fitting a linear mixed‐effect model to discern patterns in PEth elimination over time. It took intra‐ and inter‐individual variability into consideration. The algorithm was included in a two‐step decision tree, assessing whether (i) PEth values fell within the prediction interval and (ii) the slope between two PEth values was consistent with no alcohol consumption. Data for 74 participants reporting no alcohol intake during the study were used for validation. With a detection limit of 'four units spread over 14 days', the sensitivity and specificity of the decision tree was 89%. Conclusions: Claims of alcohol abstinence can be verified using a two‐step decision tree for phosphatidylethanol 16:0/18:1 values, even when those values are above the limit for 'alcohol abstinence'. [ABSTRACT FROM AUTHOR]

Objectives: To compare resource use during the last 6 months of life of individuals diagnosed with Alzheimer's disease (AD) but for whom AD was not formally identified as the underlying cause of death (dying with AD) with that of those who had AD as underlying cause of death (dying of AD). Design: Full‐population retrospective analysis. Setting: Belgium. Participants: All Belgian decedents in 2012. Measurements: We linked participants' healthcare, population, and death certificate data. Those who died of AD were selected based on underlying cause of death. Those who died with AD were selected using a validated algorithm. Results: Individuals who died of AD had less hospital use than those who died with AD; were less often admitted to a palliative care unit but received palliative home care services slightly more often; and had use of physiotherapy, noninvasive ventilation, medical imaging, sedatives, oxygen, and opioids comparable with that of those who died with AD. Conclusion: During the last 6 months of life, individuals dying of AD used fewer intensive resources such as intensive care unit, cardiopulmonary resuscitation, and invasive ventilation than those dying with AD, which suggests the effect of recognition of an end‐of‐life phase. Overall, individuals with AD rarely used palliative care services, suggesting a need for more efforts to encourage use of palliative care in individuals with AD. [ABSTRACT FROM AUTHOR]

Objective: Acute infection is the most common presentation of children to hospital. A minority of these infections are serious, but early recognition and adequate management are essential. We aimed to develop improved tools to assess children attending ambulatory hospital care, integrating clinical features with point-of-care C reactive protein (CRP).Design: Prospective observational diagnostic study.Setting and Patients: 5517 acutely ill children (1 month-16 years) presenting to 106 paediatricians at six outpatient clinics and six emergency departments in Belgium.Index Test: Point-of-care CRP alongside vital signs and objective symptoms measurements.Main Outcome: Hospital admission for >24 hours with a serious infection <5 days after presentation.Results: An algorithm was developed consisting of clinical features and CRP. This achieved 97.1% (95% CI 94.3% to 98.7%) sensitivity and 99.6% (95% CI 99.2% to 99.8%) negative predictive value, excluding serious infections in 36.4% of children. It stratifies patients into three groups based on CRP level: high-risk group with CRP >75 mg/L (26.8% risk of infection), intermediate-risk group with CRP 20-75 mg/L and at least one of seven clinical features (8.1%), and lower risk group with CRP <20 mg/L with at least one of the 11 features (3.8%). Children in intermediate-risk or low-risk groups with normal clinical assessment have 0.6% and 0.4% risk of serious infections, respectively.Conclusions: Conducting a CRP test may first enable children to be stratified into three risk groups, guiding assessment of clinical features that could be performed by junior doctors or nurses. In one-third of acutely ill children, the algorithm could exclude serious infection. Prospective validation of the algorithm is needed.Clinical Trial Registration: NCT02024282 (post-results). [ABSTRACT FROM AUTHOR]

Throughout adolescence, there is an increase in rule-breaking behavior and a decrease in behavioral school engagement. The role of teacher-student relationship quality in the development of these adjustment problems remains understudied. This study examined how adolescent-reported teacher-student affiliation and dissatisfaction and parent-reported rule-breaking behavior and behavioral engagement impact one another throughout adolescence. In addition, we examined the moderating effect of genes by means of a Biologically Informed Multilocus genetic Profile Score (BIMPS), a composite score reflecting the cumulative effect of multiple dopaminergic genes, with a higher score indicating higher dopamine signaling in the adolescent brain. We used three-year longitudinal data from 1111 adolescents (51 % boys; M age = 13.79), and their parents. Cross-lagged analyses revealed a transactional process in which adolescents who display more rule-breaking behavior and less behavioral engagement experienced increased subsequent dissatisfaction with their teachers, which in turn further increased their adjustment problems. Also, adolescents with more adjustment problems experienced decreased subsequent affiliation with their teachers. The other way around, adolescents' behavioral engagement also benefitted from positive relationships with teachers. Multi-group analyses revealed genetic moderation for behavioral engagement, but not for rule-breaking. Specifically, adolescents who had a BIMPS score coding for moderate levels of dopamine signaling (instead of high or low signaling) were most affected in their behavioral engagement when they experienced dissatisfaction with their teachers. Our study findings may guide schools in implementing interventions to create a supportive class and school environment including positive, supportive teacher-student relationships and indicate that providing a such a supportive school environment is important for all adolescents. [ABSTRACT FROM AUTHOR]

Background: The occurrence and significance of alternans of the ventricular electrogram (VEGM) in patients with an implanted cardioverter-defibrillator (ICD) has been rarely reported. Objectives and Methods: This report describes our observations of VEGM alternans documented in nine patients with an ICD (seven new cases and two previously published cases for comparison). Results: We found seven new cases of near-field VEGM alternans and added two of our previously reported examples. Catecholaminergic polymorphic ventricular tachycardia (CPVT) was diagnosed in one patient based on ICD recordings. Alternans occurred during ventricular tachycardia (VT) in eight patients. A fast sinus tachycardia could not be ruled out in one patient. Stable cycle length alternans was found in five patients. QRS alternans of the left ventricular (LV) electrogram (EGM) was recorded in all five patients who had a device for cardiac resynchronization therapy capable of sensing by the LV channel. These five cases exhibited corresponding alternans of the right ventricular (RV) EGM in three cases, none in one patient, and a questionable recording in another. Alternans of the far-field (FF) VEGM occurred simultaneously with RV EGM alternans in all four patients whose device provided an FF tracing. Conclusion: Ventricular alternans may be more common than realized in ICD patients with VT. The correlation of VEGM alternans with the surface electrocardiogram remains unknown. Although QRS alternans itself as an electrical pattern is generally benign, its cause may not be, as illustrated in our patient with CPVT. Furthermore, associated cycle length alternans or undersensing of the smaller alternans component may complicate ICD therapy. [ABSTRACT FROM AUTHOR]

Aim To compare immediate surgery to scaling and root planing ( SRP) in the treatment of advanced periodontitis focusing on the prevalence of residual pockets after treatment and cost-effectiveness (1); to elucidate the adjunctive effects of azithromycin in a second-treatment phase (2) up to 36 months. Materials and Methods Thirty-nine patients (18 males, 21 females; mean age: 54.6) received oral hygiene instructions and were randomly allocated to surgery ( n = 19) or SRP ( n = 20). Patients with residual pockets (≥6 mm) at 6 months received re-debridement of these sites and systemic azithromycin. Clinical measurements were performed at 12, 24 and 36 months whereby residual pockets underwent re-debridement. Patients were evaluated in terms of clinical response parameters and cost-effectiveness. Chair-time was used to assess the financial impact of treatment. Results Only six patients in the surgery group required additional treatment at 6 months, whereas 14 patients in the SRP underwent this therapy. Both treatment arms were equally effective in terms of clinical outcome demonstrating <2% residual pockets at 36 months. Surgery imposed an extra 746 Euro on the patient up to 6 months compared to SRP. At 36 months, 69 Euro of this amount could be offset due to the lower need for re-treatment during maintenance phase. Conclusions Surgery was ultimately associated with a significantly lower need for re-treatment during supportive care, however, at significantly higher costs over the 3 years. [ABSTRACT FROM AUTHOR]

Consonant inventories are commonly drawn to assess the phonological acquisition of toddlers. However, the spontaneous speech data that are analysed often vary substantially in size and composition. Consequently, comparisons between children and across studies are fundamentally hampered. This study aims to examine the effect of sample size on the resulting consonant inventories. A spontaneous speech corpus of 30 Dutch-speaking 2-year-olds was used. The results indicate that in order to construct and compare inventories reliably, they should be drawn from speech samples that are equally large. A new consonant inventory procedure is introduced. The implementation of this procedure demonstrates considerably less variation in inventory size across children and word positions than reported previously. This finding has important implications for clinical studies that constructed and compared inventories of typically and atypically developing children without normalizing the sample size. [ABSTRACT FROM AUTHOR]

Inland vessels move goods along waterways (canals and rivers) and they visit ports. Because of their tidal nature, vessels make use of locks to enter ports or waterways. From a port management point of view, fast access to and from the port and high utilization of locks are important objectives. Where the former relates to low inbound and outbound waiting times, the latter relates to the placement of as many vessels as possible in the lock before its operation. This article includes a case study that relates to the operation of the Van Cauwelaert lock in the port of Antwerp, Belgium. Lock operation policy is as follows: vessels wait in front of the lock for a port administrator to assign places in the lock based on knowledge of the vessels’ dimensions. As such, there is no FIFO-discipline, but a ‘group-FIFO’-discipline, i.e. if n vessels are allowed into the lock, they are the first n vessels in the arrival queue. A heuristic algorithm is formulated for the placement of vessels in the lock. This algorithm supports the decision where to place the vessel in the lock, aiming to place as many vessels as possible from the arrival queue. At the same time, it supports the decision to start a locking operation or not, based on information about vessels that are announced but which have not yet arrived at the lock's entrance. The heuristic is called a ‘less-flexibility-first’-heuristic as it looks for pseudo-placements, showing which flexibility is left for the remaining vessels after placing a vessel. This article describes the implementation of the heuristic and provides numerical examples. A comparison is made between the heuristic results and daily practice, based on real-life vessel movements through the Van Cauwelaert lock in 2002. [ABSTRACT FROM AUTHOR]