Correction to: Efficient Algorithm for Identification and Cache Based Discovery of Cloud Services

Mobile Networks and Applications - The original version of this article unfortunately contained a mistake in the author group section. Author “V. Varadarajan” should be expanded to...     

Geometrically nonlinear formulation for the axisymmetric shell elements

A geometrically nonlinear formulation using total Lagrangian approach is presented for the axisymmetric shell elements. The basic element is formulated using the co-ordinates of the mid-surface nodes and the mid-surface nodal point normals. An important aspect of the formulation presented here is that the restriction on the magnitude of the nodal rotations is eliminated. This is accomplished by retaining true nonlinear nodal rotation terms in the definition of the displacement field and the consistent derivation of the element properties based on this displacement field. The element properties are derived and presented in detail. Numerical examples are also presented to demonstrate the element behaviour and the accuracy.     

Dilatometric fragility and prediction of the viscosity curve of glass-forming liquids

Viscosity and coefficient of thermal expansion (CTE) are both crucial properties in the design of new glasses for various applications. In this work, we extend the application of dilatometry to measure two important parameters governing the viscosity of glass-forming systems, viz., glass transition temperature and fragility index. We also describe a method to determine the dilatometric fictive temperature (T_f,DIL) and present data for five unique glass compositions covering a range of fragilities spanning 38-96, which are subjected to cooling and reheating rates in the range 1-30 K/min. The results show that the glass transition temperature obtained from the dilatometric method at 10 K/min (T_g,DIL) is consistent with both viscosity-based (T_g,vis) and DSC-based measurements (T_g,DSC). It is shown that the fragility of a liquid (m_vis) can be determined by calibrating the dilatometric fragility (m_DIL) with the same empirical model as in the calorimetric approach. Put together, we have developed a reliable method to measure the fragility and predict the viscosity curves of glass-forming liquids over a wide range (eg, 10¹-10¹⁶ Pa·s) without direct viscosity measurements, while simultaneously obtaining the CTE of the glass. However, this method is not suitable for glasses with a strong tendency toward phase separation or crystallization.     

Isoparametric elemetns for cross-sepctional properties and stress analysis of beams

This paper presents an isoparametric finite element formulation for the torsion and the flexure due to end shears for the beam cross-sections of arbitrary shape. Isoparametric line elements are developed using this formulation for the beam cross-sections consisting of very thin wall open or close multicells. Isoparametric transition elements are also developed for the beam cross-sections consisting of both thin wall sections and solid like sections. Numerical examples are presented to demonstrate the accuracy and the applications of such elements.     

A novel vector-space-based lightweight privacy-preserving RFID authentication protocol for IoT environment

The Journal of Supercomputing - Internet of Things (IoT) is a novel paradigm that connects several physical devices and the cyber world over the Internet. IoT technology is growing rapidly and soon...     

Drug-eluting Ti wires with titania nanotube arrays for bone fixation and reduced bone infection

Current bone fixation technology which uses stainless steel wires known as Kirschner wires for fracture fixing often causes infection and reduced skeletal load resulting in implant failure. Creating new wires with drug-eluting properties to locally deliver drugs is an appealing approach to address some of these problems. This study presents the use of titanium [Ti] wires with titania nanotube [TNT] arrays formed with a drug delivery capability to design alternative bone fixation tools for orthopaedic applications. A titania layer with an array of nanotube structures was synthesised on the surface of a Ti wire by electrochemical anodisation and loaded with antibiotic (gentamicin) used as a model of bone anti-bacterial drug. Successful fabrication of TNT structures with pore diameters of approximately 170 nm and length of 70 μm is demonstrated for the first time in the form of wires. The drug release characteristics of TNT-Ti wires were evaluated, showing a two-phase release, with a burst release (37%) and a slow release with zero-order kinetics over 11 days. These results confirmed our system''s ability to be applied as a drug-eluting tool for orthopaedic applications. The established biocompatibility of TNT structures, closer modulus of elasticity to natural bones and possible inclusion of desired drugs, proteins or growth factors make this system a promising alternative to replace conventional bone implants to prevent bone infection and to be used for targeted treatment of bone cancer, osteomyelitis and other orthopaedic diseases.     

Integrated CMOS optical sensor for cell detection and analysis

To circumvent the complexity of the detection systems of microfluidic devices, Hartley et al. recently reported on a CMOS optical active pixel sensor (APS) for near-field detection and counting of microscopic particles. To further enhance the digital cytometric capabilities of the original sensor, we modified and utilized a dual APS-array scheme to facilitate the determination of the velocity and size of particles flowing in microfluidic channels. Our findings indicate that the prototype dual-APS sensor is capable of detecting particle velocities up to ～500 μm/s and particles with diameter in the range of 5–15 μm. The dual APS CMOS sensor, as a result of the hybrid integration with a microfluidic, provides a low cost and practical means of noninvasively monitoring the contents of microfluidic and lab-on-a-chip devices.     

Mixed modifier effects on structural,mechanical, chemical,and mechanochemical properties of sodium calcium aluminosilicate glass

Glass properties are governed by the interplay between network formers and network modifiers; for a given composition of network formers, the ratio of different cationic modifiers compensating the anionic species in the network has a profound effect, which is often nonlinear, called a mixed modifier effect (MME). We have investigated the MME of sodium (Na) and calcium (Ca) in an aluminosilicate (NCAS) glass series following the formula [Na₂O]_30−x [CaO]_x [Al₂O₃]₁₀ [SiO₂]₆₀, where x = 0, 7.5, 15, 22.5, and 30. A nonadditive trend was observed in hardness and indentation toughness, with aqueous corrosion resistance exhibiting a shift from incongruent to congruent corrosion, whereas the network structure determined by molecular dynamics simulations revealed no significant trend with composition. Additionally, the NCAS glass containing both [Na₂O] and [CaO] within an intermediate range exhibited superior resistance to wear at high humidity, a clear MME phenomenon previously only observed in soda–lime silica.     

Focused ion beam-scanning electron microscopy on solid-oxide fuel-cell electrode: Image analysis and computing effective transport properties

In the present work, microstructural and transport properties of a three-dimensional (3D) microstructure of lanthanum strontium manganite (LSM) are deduced using dual-beam focused ion beam-scanning electron microscopy (FIB-SEM) facility. A series of two-dimensional (2D) cross-sectional images are collected from the LSM sample using FIB-SEM and then reconstructed to 3D structures from the 2D images in a systematic approach. For the first time, the effect of different image processing steps including threshold value, median filter radius, morphological operators, surface triangulation, smoothing filter, etc., on porosity, internal surface area, electronic conductivity and diffusivity are studied. Variation of 33% and 25% on porosity ? and internal surface area S, respectively is observed because of improper selection of threshold value, median filter radius, and morphological operator. The number of triangular surfaces used in 3D reconstructions also varied the porosity ? and internal surface area S by 14.5% and 4.4%, respectively.Computational domains for calculating effective transport properties are generated using body-fitted cut-cell based finite volume meshes on reconstructed 3D volumes. The normalized effective transport properties are computed on computational domains reconstructed by the FIB-SEM as well as by a numerical model. For the FIB-SEM reconstruction case, the normalized effective properties in z-direction are 25-44% smaller than those properties in x and y directions. This difference is significant and reveals the anisotropy in FIB-SEM reconstructed volume compared to numerically reconstructed volume. The presence of large crater, milling direction and smaller 3D FIB-SEM reconstructed volume could be the main reasons for this local anisotropy.     

A diagnostic testing for people with appendicitis using machine learning techniques

Appendicitis is a common disease that occurs particularly often in childhood and adolescence. The accurate diagnosis of acute appendicitis is the most significant precaution to avoid severe unnecessary surgery. In this paper, the author presents a machine learning (ML) technique to predict appendix illness whether it is acute or subacute, especially between 10 and 30 years and whether it requires an operation or just taking medication for treatment. The dataset has been collected from public hospital-based citizens between 2016 and 2019. The predictive results of the models achieved by different ML techniques (Logistic Regression, Naïve Bayes, Generalized Linear, Decision Tree, Support Vector Machine, Gradient Boosted Tree, Random Forest) are compared. The covered dataset are 625 specimens and the total of the medical records that are applied in this paper include 371 males (60.22%) and 254 females (40.12%). According to the dataset, the records consist of 318 (50.88%) operated and 307 (49.12%) unoperated patients. It is observed that the random forest algorithm obtains the optimal result with an accurately predicted result of 83.75%, precision of 84.11%, sensitivity of 81.08%, and the specificity of 81.01%. Moreover, an estimation method based on ML techniques is improved and enhanced to detect individuals with acute appendicitis.