Supply chain network design using an integrated neuro-fuzzy and MILP approach: A comparative design study

In this study, an integrated supply chain (SC) design model is developed and a SC network design case is examined for a reputable multinational company in alcohol free beverage sector. Here, a three echelon SC network is considered under demand uncertainty and the proposed integrated neuro-fuzzy and mixed integer linear programming (MILP) approach is applied to this network to realize the design effectively. Matlab 7.0 is used for neuro-fuzzy demand forecasting and, the MILP model is solved using Lingo 10.0. Then Matlab 7.0 is used for artificial neural network (ANN) simulation to supply a comparative study and to show the applicability and efficiency of ANN simulation for this type of problem. By evaluating the output data, the SC network for this case is designed, and the optimal product flow between the factories, warehouses and distributors are calculated. Also it is proved that the ANN simulation can be used instead of analytical computations because of ensuring a simplified representation for this method and time saving.     

Vitamin A status of healthy children in Manisa,Turkey

Background  

Vitamin A deficiency is a major public health nutrition problem in the developing world. Even subclinical Vitamin A deficiency is associated with increased childhood mortality. Severe maternal vitamin A deficiency may cause increased mortality in the first months of life. There have been a limited number of studies regarding vitamin A status in Turkey. The aim of this study was to assess vitamin A status of healthy children in Manisa, Turkey.     

Stabilization of subbase layer materials with waste pumice in flexible pavement

In the present study, the usability of the pumice of the Isparta-Karakaya those categorized in the light aggregate class, have been examined in terms of stabilization material in the subbase considering volumetric unit weight.     

EDTriangles: a high-speed triangle detection algorithm with a false detection control

We present a high-speed method for triangular object detection. The proposed method utilizes the recently developed, real-time edge segment detection algorithm, Edge Drawing; hence, the name EDTriangles, which consists of a detection stage and a validation stage. In the detection stage, EDTriangles extracts edge segments from the image using Edge Drawing and converts these edge segments into line segments, which are then converted into line pairs according to the angles between the line segments and the distance between their endpoints. Next, the line pairs are combined together using some heuristics to generate many triangle candidates, some of which are valid detections and some invalid. Finally, in the validation stage the candidate triangles are validated using the Helmholtz principle and number of false alarms computation to eliminate false detections. Experimental results show that EDTriangles runs very fast, detects various types of triangular objects ranging from narrow to wide-angled triangles and offers a higher detection performance compared to some of the well-known triangle detection algorithms found in the literature.     

Magnetic Anomalies and Electronic Structure of Ce<Subscript>2</Subscript>Cu<Subscript>2</Subscript>Mg and Ce<Subscript>2</Subscript>Pd<Subscript>2</Subscript>Mg

The intermetallic compounds RE ₂Cu₂Mg and RE ₂Pd₂Mg (RE=La, Ce) were prepared and characterized by magnetic susceptibility and heat-capacity measurements. They crystallize with an ordered U₃Si₂ type structure (space group P4/mbm) and the cerium compounds contain stable trivalent cerium ions, which undergo antiferromagnetic ordering at ∼7.5 and ∼4 K, respectively. In high magnetic fields Ce₂Cu₂Mg exhibits spin reorientation with critical field strength of 40 kOe at 5 K. The data are compared to the non-magnetic isotypic compounds La₂ T ₂Mg (T=Cu, Ni, Pd) and to the already reported intermediate valent Ce₂Ni₂Mg.     

Synthesis and Characterization of Konjac Gum/Polyethylene Glycol-Silver Nanoparticles and their Potential Application as a Colorimetric Sensor for Hydrogen Peroxide

Journal of Inorganic and Organometallic Polymers and Materials - Green and low-cost synthesis strategies for ultrasonic preparation of polymer blend matrix-based silver nanoparticles (Ag NPs) and...     

Design of the polyacrylonitrile-reduced graphene oxide nanocomposite-based non-enzymatic electrochemical biosensor for glucose detection

With the advantages of developed electronic devices, various biosensor applications have become attractive issues with excellent electrochemical performances against biomarkers and molecules in biomedical applications. In this study, novel polyacrylonitrile (PAN)-reduced graphene oxide (rGO) nanocomposite-based non-enzymatic electrochemical biosensors were prepared to investigate the detection performance of the glucose. The PAN-rGO nanocomposite-based biosensor detected glucose with a high sensitivity and stability due to enhanced redox mechanism arising from rGO additive. PAN-rGO nanocomposite-based biosensor detected glucose in (0.75–12) mM with a high sensitivity of 49 µAmM^?1 cm^?2 (2.5 times higher than PAN-based sensor). Concentration–response graphs correlating the non-enzymatic electrochemical signal to glucose concentration revealed a low limit of detection (LOD) of 0.6 mM within 1-min voltammetric cycle. The selectivity results confirmed a significant preferential response of the proposed PAN-rGO nanocomposite-based biosensor for glucose against possible interfering compounds. The proposed PAN-rGO nanocomposite-based biosensor has a great potential to be used as a nanostructured platform for detection of glucose in phosphate-buffered saline (pH 7.4) solution with high sensitivity, selectivity, stability, reproducibility, and fast response properties.

     

Conjugate heat transfer characterization in cooling channels

Cooling technology of gas turbine blades,primarily ensured via internal forced convection,is aimed towards withdrawing thermal energy from the airfoil.To promote heat exchange,the walls of internal cooling passages are lined with repeated geometrical flow disturbance elements and surface non-uniformities.Raising the heat transfer at the expense of increased pressure loss;the goal is to obtain the highest possible cooling effectiveness at the lowest possible pressure drop penalty.The cooling channel heat transfer problem involves convection in the fluid domain and conduction in the solid.This coupled behavior is known as conjugate heat transfer.This experimental study models the effects of conduction coupling on convective heat transfer by applying iso-heat-flux boundary condition at the external side of a scaled serpentine passage.Investigations involve local temperature measurements performed by Infrared Thermography over flat and ribbed slab configurations.Nusselt number distributions along the wetted surface are obtained by means of heat flux distributions,computed from an energy balance within the metal domain.For the flat plate experiments,the effect of conjugate boundary condition on heat transfer is estimated to be in the order of 3%.In the ribbed channel case,the normalized Nusselt number distributions are compared with the basic flow features.Contrasting the findings with other conjugate and convective iso-heat-flux literature,a high degree of overall correlation is evident.     

PVA:Nano-eggshell microcomposite as an energy storage material for supercapacitors

Journal of Materials Science: Materials in Electronics - The development and advantages of wearable flexible electronics have become attractive issues with excellent electrochemical performances in...     

On modelling of surface tension of CMC-α-Fe2O3 nanoparticles by fuzzy-hybrid approach: A comparison study

Surface tension is one of the most important rheological parameters of nanoliquids. It influences the thermophysical and mass transfer properties of nanostructures. Accurate estimation of the surface tension from operating variables is critical for determining optimal production processes. However, the challenges of producing nanoparticles and measuring their properties introduce experimental errors in the data used for mathematical modelling. Crisp regression approaches provide adequate representation of the data, but they do not provide information about the experimental uncertainty. In this study, a fuzzy-hybrid approach is proposed for mathematical modelling of surface tension of carboxymethyl cellulose/chitosan-α-Fe₂O₃ nanoparticles. Then, the proposed model is compared with a crisp model from a previous study. Error analysis is conducted to validate the constructed fuzzy model. It is observed that the fuzzy-hybrid modelling approach has yielded significantly lower error values (a 60%–90% improvement in all error metrics on average), and thus, it is superior to the crisp approach. This study contributes to the subject of modelling rheological properties. It is shown that the fuzzy-hybrid approach has impressive potential to be utilized for modelling the rheological properties of nanostructures.