APPLICATION OF RESPONSE SURFACE METHODOLOGY FOR THE MAXIMIZATION OF CONCORA CRUSH RESISTANCE OF PAPERBOARD

Response surface methodology is often used by researchers in different fields to determine the optimum values for controlled variables to maximize or minimize the response variables. Either maximization or minimization might be necessary depending on the response property. For example, if the response variable represents the yield of a process, maximization could be necessary; on the other hand, if the response variable is the biological oxygen demand (BOD) of an effluent the aim would definitely be minimization

Response surface methodology can be used two ways. It can be applied to the full-scale production or it can be scaled to a laboratory or the pilot plant. When applied to the full-scale production, the method is known as evolutionary operation (EVOP). EVOP is the continuous optimization of a process. The optimum conditions in a production plant can change depending on many factors such as raw material, ambient temperature, and equipment wear. Therefore, controlled variables should be optimized continuously to keep the response variable as close as possible to the maximum or minimum value. Hence, controlled variables are systematically changed around a center point to depict any shift of the response variable from the extreme. A thorough discussion of EVOP is given by Box, Evolutionary Operation: A Method for Increasing Industrial Productivity, Appl. Statist., 6, 81-101 (1957).     

Dyes from the leaves of deciduous plants with a high tannin content for wool

The aqueous leaf extracts of five different deciduous plants, namely, silver oak, flame of the forest, tanner’s senna, wattle and serviceberry, were used on their own and in combination with aluminium sulphate, stannous chloride and ferrous sulphate to dye wool by a simultaneous mordanting technique. The washing and light fastness properties of the developed shades were moderate to good. Based on the CIE 2000 spectral colour coordinate values (K/S, ΔL, Δa, Δb and ΔE), the developed shades were classified into four groups: yellow/brown, yellow, orange and dark grey. The use of aluminium sulphate gave medium shades (K/S = 8.24), while the stannous chloride and ferrous sulphate mordants provided deep shades (K/S = 30.5). Statistical analyses have shown that only the type of mordant and not the dye source significantly influenced the development of colour on wool. Hence, it was theoretically possible to use five selected leaves as a single mixture to produce four different colours on wool.     

Electron Microscopy of Annealed (Ni,Zn,Co)Fe2O4

( Ni,Zn)Fe₂O₄ samples containing small amounts of Co were characterized in a transmission electron microscope to ascertain the micro structural changes accompanying low-temperature oxidation of the samples. Although no new features resulting from oxidation were observed, prominent surjace reduction occurred in the thin foil specimens. Formation and growth of Ni particles on the ferrite surface are explained using the heats of formation of the oxides.²     

Towards an Environmentally Acceptable Heterogeneous Catalytic Method of Producing Adipic Acid by the Oxidation of Hydrocarbons in Air

A survey is given of the catalytic methods potentially available for the production of adipic acid by the oxidation of readily available hydrocarbon precursors under environmentally benign conditions. Encouraging results are reported using H₂O₂ as oxidant and microporous FeAlPO-5 as catalyst at moderate temperatures.     

Surface wavelength content based clustering using neural networks for manufacturing process mapping

Manufacturing processes produce a unique texture on the surface that serves as a fingerprint of the process. It is possible to provide feedback to the process by studying the surfaces carefully. Analytical techniques such as Fourier analysis and digital filters are commonly used to characterize surface profiles. Parameters extracted from filtered profiles are monitored to detect variations in the process. This requires the development of an inference engine to map metrology parameters to manufacturing process parameters. This paper presents an artificial neural network (ANN) based inference engine for providing process feedback with surface finish input. Parameters such as R_a and W_a as well as advanced wavelet based features are extracted from surface finish data collected from a crankshaft manufacturing line and fed as input to the neural network. This input is then clustered using a competitive neural network trained in unsupervised mode. The resulting clusters are analyzed and discussed. The network is then tested with new data to evaluate the quality of the clusters previously generated and to demonstrate the applicability of this technique for detecting process variations.     

An Efficient Framework for Utilizing Underloaded Servers in Compute Cloud

In cloud data centers, the consolidation of workload is one of the phases during which the available hosts are allocated tasks. This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the Service Level Agreement (SLA). To consolidate the workloads, the hosts are segregated into three categories: normal hosts, under-loaded hosts, and overloaded hosts based on their utilization. It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish. Threshold values were proposed in the literature to detect this scenario. The current study aims to improve the existing methods that choose the underloaded hosts, get rid of Virtual Machines (VMs) from them, and finally place them in some other hosts. The researcher proposes a Host Resource Utilization Aware (HRUAA) Algorithm to detect those underloaded and place its virtual machines on different hosts in a vibrant Cloud environment. The mechanism presented in this study is contrasted with existing mechanisms empirically. The results attained from the study establish that numerous hosts can be shut down, while at the same time, the user's workload requirement can also be met. The proposed method is energy-efficient in workload consolidation, saves cost and time, and leverages active hosts.     

Opposition Based Joint Grey Wolf-Whale Optimization Algorithm Based Attribute Based Encryption in Secure Wireless Communication

Wireless Personal Communications - One of the applications of Sparse Linear Wireless Sensor Networks is environmental monitoring. In these networks, sensors are deployed in sensitive and strategic...     

Design of backpropagated neurocomputing paradigm for Stuxnet virus dynamics in control infrastructure

Neural Computing and Applications - In the present study, a novel application of backpropagated neurocomputing heuristics (BNCH) is presented for epidemic virus model that portrays the Stuxnet...     

Laser-treated austenitic steel and nickel alloy for human implants

The recent research in biocompatible materials has been useful in replacing and supporting the fractured natural human bones/joints. Under some condition, negative reaction like release of ions from the bare metal toward the human body fluid leads to corrosion. In this proposed research paper, the biocompatibility of the laser surface-modified austenitic stainless steel (SS316L) and nickel-based superalloy (Inconel 718) was studied. The investigation on laser-modified surfaces is evaluated through electrochemical polarization analysis using simulated body fluid (SBF). The samples subjected to electrochemical polarization analysis were characterized by optical image analysis, SEM, EDS, and XRD analysis. It was inferred that laser surface-modified materials provided enhanced corrosion resistance and bare nickel alloy is more susceptible to corrosion by SBF.