Slab waveguide with conducting interfaces as an efficient optical sensor: TE case

In this paper, three-layer slab waveguide structure is treated for optical sensing applications. Four waveguide configurations including different guiding films and analytes are assumed. A conducting two-dimensional free charge layers with a surface conductivity is assumed to exist at the substrate/film and film/cladding interfaces. The sensing sensitivity of the proposed structure to any changes in an analyte refractive index uniformly distributed in the cladding layer is investigated. Positive as well as negative surface conductivities are considered. It is found that utilizing positive surface conductivity can enhance the sensitivity, whereas using negative values of the surface conductivity reduces the sensitivity.     

Friction and Wetting Transitions of Magnetic Droplets on Micropillared Superhydrophobic Surfaces

Reliable characterization of wetting properties is essential for the development and optimization of superhydrophobic surfaces. Here, the dynamics of superhydrophobicity is studied including droplet friction and wetting transitions by using droplet oscillations on micropillared surfaces. Analyzing droplet oscillations by high‐speed camera makes it possible to obtain energy dissipation parameters such as contact angle hysteresis force and viscous damping coefficients, which indicate pinning and viscous losses, respectively. It is shown that the dissipative forces increase with increasing solid fraction and magnetic force. For 10 µm diameter pillars, the solid fraction range within which droplet oscillations are possible is between 0.97% and 2.18%. Beyond the upper limit, the oscillations become heavily damped due to high friction force. Below the lower limit, the droplet is no longer supported by the pillar tops and undergoes a Cassie–Wenzel transition. This transition is found to occur at lower pressure for a moving droplet than for a static droplet. The findings can help to optimize micropillared surfaces for low‐friction droplet transport.     

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.     

A Memetic Algorithm for staff scheduling problem in airport security service

The staff scheduling problem is widely studied in Operational Research. Various surveys are available in the literature dealing with this problem which concerns various objectives and various constraints. In this article, we present a staff scheduling problem in airport security service. First, a modeling of the problem, and a representation of solutions are shown. The problem is solved in three steps, days-off scheduling, shift scheduling, and staff assignment. We focus on the last step, by providing a Memetic Algorithm (MA) which merged an Evolutionary Algorithm and Local Search techniques. We propose a chromosome encoding, a crossover operator and a combined neighborhood function, specially dedicated to this staff assignment problem. Besides providing better solutions than software currently used, this algorithm provides up to 50% of improvement from initial feasible solutions.     

Detecting,classifying, and tracing non-functional software requirements

In this paper, we describe a novel unsupervised approach for detecting, classifying, and tracing non-functional software requirements (NFRs). The proposed approach exploits the textual semantics of software functional requirements (FRs) to infer potential quality constraints enforced in the system. In particular, we conduct a systematic analysis of a series of word similarity methods and clustering techniques to generate semantically cohesive clusters of FR words. These clusters are classified into various categories of NFRs based on their semantic similarity to basic NFR labels. Discovered NFRs are then traced to their implementation in the solution space based on their textual semantic similarity to source code artifacts. Three software systems are used to conduct the experimental analysis in this paper. The results show that methods that exploit massive sources of textual human knowledge are more accurate in capturing and modeling the notion of similarity between FR words in a software system. Results also show that hierarchical clustering algorithms are more capable of generating thematic word clusters than partitioning clustering techniques. In terms of performance, our analysis indicates that the proposed approach can discover, classify, and trace NFRs with accuracy levels that can be adequate for practical applications.     

Microfluidic multi-target sorting by magnetic repulsion

In magnetophoresis-based microfluidic systems, the free-flow sorting is achieved by incrementally navigating the magnetic target toward a designated outlet. This is typically enabled using high-gradient magnetic concentrators (HGMCs), axially aligned or slightly slanted with the streaming sample flow. Such axial and incremental magnetic manipulation critically constraints the throughput and the number of targets that can be sorted simultaneously. To overcome these constraints, we present an alternative repulsion-based sorting method. The repulsion force is due that induced, over a limited angular expanse, around a single ferromagnetic wire. The wire is positioned transversally against the focused sample flow. Differentially repelled by the repulsive force, each target deflects from its focused path to follow a ribbon-like trajectory that leads to a spatially addressable outlet. The mediated sorting takes place more rapidly and is confined to the region facing the transversal wire. More importantly, the introduced concept design allows for a throughput that is geometrically scalable with the length of the wire. The functionality of the systems is demonstrated experimentally and numerically to yield the simultaneous and complete multi-target sorting of two and more magnetic beads.     

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.     

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.     

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.