Probability of detecting and quantifying faecal contaminations of drinking water by periodically sampling for E. coli: a simulation model study

Drinking water supply companies monitor the presence of Escherichia coli in drinking water to verify the effectiveness of measures that prevent faecal contamination of drinking water. Data are lacking, however, on the sensitivity of the monitoring programmes, as designed under the EU Drinking Water Directive. In this study, the sensitivity of such a monitoring programme was evaluated by hydraulic model simulations of contamination events and calculations of the detection probability of the actual sampling programme of 2002. In the hydraulic model simulations of 16-h periods of 1l h(-1) ingress of untreated domestic sewage, the spread of the contamination through the network and the E. coli concentration dynamics were calculated. The results show that when large parts of the sewage reach reservoirs, e.g. when they originate from the treatment plant or a trunk main, mean detection probabilities are 55-65%. When the contamination does not reach any of the reservoirs, however, the detection probability varies from 0% (when no sampling site is reached) to 13% (when multiple sites are reached). Mean detection probabilities of nine simulated ingress incidents in mains are 5.5% with an SD of 6.5%. In reality, these detection probabilities are probably lower as the study assumed no inactivation or clustering of E. coli, 100% recovery efficiency of the E. coli detection methods and immediate mixing of contaminations in mains and reservoirs. The described method provides a starting point for automated evaluations and optimisations of sampling programmes.     

Reliability design of multibody systems using sample-based extreme value theory

A multibody system can be modeled with multiple parameters such as mass, stiffness, damping, and length. Even though such parameters are frequently assumed to be deterministic, they are not because of various factors such as manufacturing tolerance, material irregularity, fatigue, and wear. Because the performance of a multibody system depends on its parameters, parameter uncertainties result in system performance uncertainty. Probability density functions (PDFs) of uncertain parameters can be identified based on their populations. In practical engineering problems, however, it is almost impossible to enumerate the populations of all parameters. Therefore in this study, we propose a sample-based reliability design method using an extreme value theory. The effectiveness and accuracy of the proposed method is validated with three explicit functions and two multibody systems.     

Hyperspectral analysis of mangrove foliar chemistry using PLSR and support vector regression

Hyperspectral remote sensing enables the large-scale mapping of canopy biochemical properties. This study explored the possibility of retrieving the concentration of nitrogen, phosphorus, potassium, calcium, magnesium, and sodium from mangroves in the Berau Delta, Indonesia. The objectives of the study were to (1) assess the accuracy of foliar chemistry retrieval, (2) compare the performance of models based on support vector regression (SVR), i.e. ?-SVR, ν-SVR, and least squares SVR (LS-SVR), to models based on partial least squares regression (PLSR), and (3) investigate which spectral transformations are best suited. The results indicated that nitrogen could be successfully modelled at the landscape level (R² = 0.67, root mean square error (RMSE) = 0.17, normalized RMSE (nRMSE) = 15%), whereas estimations of P, K, Ca, Mg, and Na were less encouraging. The developed nitrogen model was applied over the study area to generate a map of foliar N variation, which can be used for studying ecosystem processes in mangroves. While PLSR attained good results directly using all untransformed bands, the highest accuracy for nitrogen modelling was achieved using a combination of LS-SVR and continuum-removed derivative reflectance. All SVR techniques suffered from multicollinearity when using the full spectrum, and the number of independent variables had to be reduced by singling out the most informative wavelength bands. This was achieved by interpreting and visualizing the structure of the PLSR and SVR models.     

A Novel Internet of Medical Thing Cryptosystem Based on Jigsaw Transformation and Ikeda Chaotic Map

Image encryption has attracted much interest as a robust security solution for preventing unauthorized access to critical image data. Medical picture encryption is a crucial step in many cloud-based and healthcare applications. In this study, a strong cryptosystem based on a 2D chaotic map and Jigsaw transformation is presented for the encryption of medical photos in private Internet of Medical Things (IoMT) and cloud storage. A disorganized three-dimensional map is the foundation of the proposed cipher. The dispersion of pixel values and the permutation of their places in this map are accomplished using a nonlinear encoding process. The suggested cryptosystem enhances the security of the delivered medical images by performing many operations. To validate the efficiency of the recommended cryptosystem, various medical image kinds are used, each with its unique characteristics. Several measures are used to evaluate the proposed cryptosystem, which all support its robust security. The simulation results confirm the supplied cryptosystem’s secrecy. Furthermore, it provides strong robustness and suggested protection standards for cloud service applications, healthcare, and IoMT. It is seen that the proposed 3D chaotic cryptosystem obtains an average entropy of 7.9998, which is near its most excellent value of 8, and a typical NPCR value of 99.62%, which is also near its extreme value of 99.60%. Moreover, the recommended cryptosystem outperforms conventional security systems across the test assessment criteria.     

Cross-sectional design with curvature constraints

A practical example of B-spline curve control points manipulation for the geometric construction of a free form shape is presented. Elements of a cross-sectional design methodology are used in conjunction with a skinning type operator for the definition of a B-spline surface. Skinning process is well established in the CAD community, but further difficulties arise in producing smooth surfaces under constraints. This paper attempts to overcome the fairness problem by choosing an appropriate solution where the execution time has to be reasonably short. Main results include an industrial application in a preliminary aerodynamic design cycle where manufacturing tolerances defined by smoothness criteria are maintained.     

Editorial: Open Source and Empirical Software Engineering

Editorial Commentary

Editorial: Open Source and Empirical Software Engineering     

A survey on developing publish/subscribe middleware over wireless sensor/actuator networks

Publish/subscribe (Pub/Sub) interaction paradigm is receiving more attention in commercial and academic research nowadays. It is an effective interaction scheme for large-scale distributed systems due to its ability of decoupling communicating entities in time, space, and synchronization. The decoupling properties are well-suited for Wireless Sensor Network (WSN) applications because of their special characteristics such as data-centricity, dynamicity, and many-to-many communications. Many studies have been conducted to adapt Pub/Sub communication model to WSN. In this paper, we review the Pub/Sub interaction paradigm in the context of WSN. Moreover, we classify, analyze and synthesize different Pub/Sub based solutions proposed recently for WSN and discuss the open problems and new research directions in this area. Also, we propose a new reference model for pub/sub middleware in wireless sensor and actuator networks. To the best of our knowledge this is the first survey on this specific subject.     

Thermomechanical Analysis of (Cu0.5Tl0.5)-1223 Substituted by Pr and La

The thermomechanical analysis (TMA) of Cu 0.5 Tl 0.5 Ba 2 Ca 2 x R x Cu 3 O 10 δ,where R=Pr and La,with 0.0≤x≤0.15,was carried out in temperature range from 450 to 1145 K.The samples were prepared by singlestep solid state reaction technique.The prepared samples were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM).The superconductivity of the prepared samples was investigated by electrical resistivity measurement.The results showed that low substitution content enhanced the (Cu 0.5 Tl 0.5)1223 phase formation,while the higher substitution content degraded this phase.The higher superconducting transition temperatures T c were found to be 114 K and 109 K at x= 0.025 for Pr-and La-substitutions,respectively.The average linear thermal expansion coefficient increased as x increased,while the shrinkage temperature decreased as x increased.Those results were emphasized by porosity and Vickers microhardness calculations.Debye temperature θ D was calculated from the linear thermal expansion coefficient data and correlated to T c to estimate the electron-phonon coupling λ ep.