An ASCII File Format for Materials Properties Database Import and Export

The industrial characterization of the machinability of metals and alloys has always been a very arbitrarily defined property, subject to the selection of various reference or test materials; and the adoption of rather naive and misleading interpretations and standards. However, it seems reasonable to assume that with the present state of knowledge of materials properties, and the current theories of solid state physics, more basic guidelines for machinability characterization might be established on the basis of the residual machined microstructures. This approach was originally pursued by Draper; and our presentation here will simply reflect an exposition and extension of this research.The technique consists initially in the production of machined chips of a desired test material on a horizontal milling machine with the workpiece (specimen) mounted on a rotary table vice. A single cut of a specified depth is taken from the workpiece (0.25 in. wide) each at a new tool location.

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National Competency Standard(NCS) using import and export management training courses for the impact on educational outcomes research in e-Trade period

The e-Business Studies ◽

10.15719/geba.16.4.201508.413 ◽

2015 ◽

Vol 16 (4) ◽

pp. 413-433

Author(s):

Jason Chung

Keyword(s):

Outcomes Research ◽

Educational Outcomes ◽

Management Training ◽

Training Courses ◽

Import And Export ◽

The Impact

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A COMPARATIVE STUDY BETWEEN UNIVARIATE AND BIVARIATE TIME SERIES MODELS FOR CRUDE PALM OIL INDUSTRY IN PENINSULAR MALAYSIA

MALAYSIAN JOURNAL OF COMPUTING ◽

10.24191/mjoc.v5i1.6760 ◽

2020 ◽

Vol 5 (1) ◽

pp. 374

Author(s):

Pauline Jin Wee Mah ◽

Nur Nadhirah Nanyan

Keyword(s):

Time Series ◽

Palm Oil ◽

Moving Average ◽

Forecast Accuracy ◽

Peninsular Malaysia ◽

Time Series Models ◽

Crude Palm Oil ◽

Univariate Time Series ◽

Import And Export ◽

Bivariate Time Series

The main purpose of this study is to compare the performances of univariate and bivariate models on four time series variables of the crude palm oil industry in Peninsular Malaysia. The monthly data for the four variables, which are the crude palm oil production, price, import and export, were obtained from Malaysian Palm Oil Board (MPOB) and Malaysian Palm Oil Council (MPOC). In the first part of this study, univariate time series models, namely, the autoregressive integrated moving average (ARIMA), fractionally integrated autoregressive moving average (ARFIMA) and autoregressive autoregressive (ARAR) algorithm were used for modelling and forecasting purposes. Subsequently, the dependence between any two of the four variables were checked using the residuals’ sample cross correlation functions before modelling the bivariate time series. In order to model the bivariate time series and make prediction, the transfer function models were used. The forecast accuracy criteria used to evaluate the performances of the models were the mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE). The results of the univariate time series showed that the best model for predicting the production was ARIMA while the ARAR algorithm were the best forecast models for predicting both the import and export of crude palm oil. However, ARIMA appeared to be the best forecast model for price based on the MAE and MAPE values while ARFIMA emerged the best model based on the RMSE value. When considering bivariate time series models, the production was dependent on import while the export was dependent on either price or import. The results showed that the bivariate models had better performance compared to the univariate models for production and export of crude palm oil based on the forecast accuracy criteria used.

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Re-Programming Hydrogel Properties using a Fuel-driven Reaction Cycle

10.26434/chemrxiv.9985334.v2 ◽

2019 ◽

Author(s):

Nishant Singh ◽

Bruno Lainer ◽

Georges Formon ◽

Serena De Piccoli ◽

Thomas Hermans

Keyword(s):

Methionine Oxidation ◽

Guanosine Triphosphate ◽

Control Reaction ◽

Reaction Cycle ◽

Materials Properties ◽

Assembly Kinetics ◽

Control Assembly ◽

Indispensable Tool ◽

Reaction Cycles ◽

Non Equilibrium

Nature uses catalysis as an indispensable tool to control assembly and reaction cycles in vital non-equilibrium supramolecular processes. For instance, enzymatic methionine oxidation regulates actin (dis)assembly, and catalytic guanosine triphosphate hydrolysis is found in tubulin (dis)assembly. Here we present a completely artificial reaction cycle which is driven by a chemical fuel that is catalytically obtained from a ‘pre-fuel’. The reaction cycle controls the disassembly and re-assembly of a hydrogel, where the rate of pre-fuel turnover dictates the morphology as well as the mechanical properties. By adding additional fresh aliquots of fuel and removing waste, the hydrogels can be re-programmed time after time. Overall, we show how catalysis can control fuel generation to control reaction / assembly kinetics and materials properties in life-like non-equilibrium systems.

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