Cost-minimization analysis of a working vacation queue with N-policy and server breakdowns

This paper investigates the N-policy M/M/1 queueing system with working vacation and server breakdowns. As soon as the system becomes empty, the server begins a working vacation. The server works at a lower service rate rather than completely stopping service during a vacation period. The server may break down with different breakdown rates during the idle, working vacation, and normal busy periods. It is assumed that service times, vacation times, and repair times are all exponentially distributed. We analyze this queueing model as a quasi-birth–death process. Furthermore, the equilibrium condition of the system is derived for the steady state. Using the matrix-geometric method, we find the matrix-form expressions for the stationary probability distribution of the number of customers in the system and system performance measures. The expected cost function per unit time is constructed to determine the optimal values of the system decision variables, including the threshold N and mean service rates. We employ the particle swarm optimization algorithm to solve the optimization problem. Finally, numerical results are provided, and an application example is given to demonstrate the applicability of the queueing model.     

Hygrothermal deformation of orthotropic nanoplates based on the state-space concept

This paper deals with the investigation of the effect of hygrothermal conditions on the bending of nanoplates using Levy type solution model employing the state-space concept. The nanoplates are assumed to be subjected to a hygrothermal environment. The two-unknown function plate theory is used to derive the governing differential equations on the basis of Eringen's nonlocal elasticity theory. The governing equations contain the small scale effect as well as hygrothermal and mechanical effects. These equations are converted into a set of first-order linear ordinary differential equations with constant coefficients. Analytical solution of bending response for nanoplates under combinations of simply supported, clamped and free boundary conditions is obtained. Comparison of the results with those being in the open literature is made. The influences played by small scale parameter, temperature rise, the degree of moisture concentration, boundary conditions, plate aspect ratio and side-to-thickness ratio are studied.     

Evaluation of an Nd doping effect on characteristic properties of tin oxide

In the present work, transparent and conductive Nd doped SnO₂ thin films were deposited via spray pyrolysis. Crystallographic, morphological, optical and electrical characterizations of SnO₂ were researched as a function of Nd doping. The XRD analysis indicated the films had tetragonal cassiterite tin oxide structure and (211) preferential direction for NdTO-0, NdTO-1, NdTO-2 and NdTO-3 samples changed to (110) plane for NdTO-4 and NdTO-5 samples. The crystalline size and strain analysis were made by using a Williamson–Hall method. The SEM micrographs showed that all films had homogenously scattered pyramidal and small densely nanoparticles. The optical analysis indicated optical band gap value of undoped film increased with 1 at% Nd doping and then it decreased with more Nd content. The Hall measurements indicated that the highest electrical conductivity was obtained for 2 at% Nd doping content.     

Discovery of path-attribute dependency in manufacturing environments: A process mining approach

The more knowledge industrial practitioners detain of their production processes, the more they are capable of performing process improvements. Nonetheless, there may exist process characteristics and dependencies that are not easily extractable from business models, such as routing dependent attributes. This paper introduces an algorithm-driven framework to establish whether process path decisions influence the attributes in non-direct sequences, e.g., deploying machine A instead of machine B affects the % of rejected parts on the process, 4 stages down the line. This problem is shown to bears similarities with sequential pattern mining problems. The basis of the solution framework relies on process mining and data mining techniques. The approach proposed is applied on a real industrial log, unveiling deficiencies in the system and providing further improvement recommendations.     

Classification and regression models of audio and vibration signals for machine state monitoring in precision machining systems

We present a data-driven method for monitoring machine status in manufacturing processes. Audio and vibration data from precision machining are used for inference in two operating scenarios: (a) variable machine health states (anomaly detection); and (b) settings of machine operation (state estimation). Audio and vibration signals are first processed through Fast Fourier Transform and Principal Component Analysis to extract transformed and informative features. These features are then used in the training of classification and regression models for machine state monitoring. Specifically, three classifiers (K-nearest neighbors, convolutional neural networks and support vector machines) and two regressors (support vector regression and neural network regression) were explored, in terms of their accuracy in machine state prediction. It is shown that the audio and vibration signals are sufficiently rich in information about the machine that 100% state classification accuracy could be accomplished. Data fusion was also explored, showing overall superior accuracy of data-driven regression models.     

Investigation on low-temperature sintered AlN nanoceramics with high thermal conductivity

The aim of this research was to investigate the effect of sintering additive and relatively low-sintering temperature on the thermal conductivity of aluminum nitride nanoceramic. While using nanosized AlN powder and liquid-phase sintering additives, the various sintering processes were performed at temperatures 1400 and 1500°C for several hours. In the analysis methods, thermal conductivity (K) and thermal diffusivity (α) were measured using thermal conductivity analyzer (Hot Disk), scanning electron microscope (SEM) was used to observe the surface morphology of the microstructure, x-ray diffraction analyzer (XRD) to analyze the grain size and crystal structure, Raman spectroscopy (Raman) emission spectrum was analyzed to identify the material microstructure and the densities of AlN specimens were measured by Archimedes method. It was found that the thermal conductivity is related to the densification of nanosize low-temperature sintered material, which can be controlled by additives and sintering temperature. With Y₂O₃ sintering add, the densification of AlN for low-temperature sintering increased by the factor of ～5% to ～12%, and the thermal conductivity was enhanced by 25%. The relative density observed in this research is about 78%-84%, and the thermal conductivity measured is in the range of 9-14 W/mK.     

Dihydroartemisinin–Bile Acid Hybridization as an Effective Approach to Enhance Dihydroartemisinin Anticancer Activity

A series of hybrid compounds based on natural products—bile acids and dihydroartemisinin—were prepared by different synthetic methodologies and investigated for their in vitro biological activity against HL-60 leukemia and HepG2 hepatocellular carcinoma cell lines. Most of these hybrids presented significantly improved antiproliferative activities with respect to dihydroartemisinin and the parent bile acid. The two most potent hybrids of the series exhibited a 10.5- and 15.4-fold increase in cytotoxic activity respect to dihydroartemisinin alone in HL-60 and HepG2 cells, respectively. Strong evidence that an ursodeoxycholic acid hybrid induced apoptosis was obtained by flow cytometric analysis and western blot analysis.     

Ca2+ enhances algal photolysis hydrogen production by improving the direct and indirect pathways

In this study, Ca²⁺ was applied to enhance the photolysis H₂ production of Chlamydomonas reinhardtii grown in pure culture or co-cultivated with bacterium. With addition of Ca²⁺, the chlorophyll and protein contents in algal cells were maintained at high levels and the reactive oxygen species (ROS) were scavenged to tolerable levels by activities of catalase (CAT) and superoxide dismutase (SOD). High chlorophyll and low ROS are benefit to protect the photosystem II (PS II) activity that responsible for the direct photolysis H₂ production. Moreover, addition of Ca²⁺ was able to promote the acetic acid assimilation as well as the starch synthesis. The starch degradation, in return, contributed to the H₂ production via the indirect photolysis pathway. Based on the improvements of direct and indirect photolysis pathways, the H₂ production of algae grown in co-cultivation adding with 5 mM Ca²⁺ reached a maximum value of 306 mL L⁻¹, which was 2.4 times higher than the production without Ca²⁺ addition. This study gives an efficient and easy strategy to improve the algal photolysis H₂ production, and gets an insight into the mechanisms of the improvement.     

Structural modification of aminoclay for catalytic applications

Abstract

An eco-friendly catalyst system was synthesized using three step reaction. The Cu nanoparticles bridged aminoclay catalyst was analyzed using various analytical techniques. The structure of the catalyst was confirmed by FTIR and XRD. The synthesized catalyst system was used for the reduction of p-nitrophenol (NP), Cr(VI), and fluorescein (Flur) dye individually, as well as in their mixture forms. The k_app value was computed to access the efficiency of the catalyst. The results indicated that the k_app value of the individual system is higher than that of the mixture systems due to the absence of the complex formation reaction. The catalytic performance of the catalyst was also tested for the Schiff base (SB) formation between poly(ethyleneglycol) (PEG) and aniline (ANI) in an oxygen atmosphere. The ¹H-NMR spectroscopy result indicates that the present catalyst system produced 86% yield.