LNG Tank Automation at Floating Storage Unit to Maximize Regasification Product at Peninsular Malaysia

2019 ◽  
Author(s):  
Mimi Juazlin M Jaini ◽  
Tn Arif Hussaini Tn Harun ◽  
Silvya Dewi Rahmawati ◽  
Bobby Suryajaya ◽  
Mahanum Muhammad
2019 ◽  
Vol 10 (02) ◽  
pp. 1-7
Author(s):  
Aan Febriansyah ◽  
Muslim Fathillah ◽  
Nurdin Nurdin

Nowaday time indicator as hour and calendar constitutes necessary for thing a lot of person to trip routines. In general, the clock and the calendar can only be seen by normal people. People with special needs, its example is blind will have difficulty in using the clock and the calendar Get bearing with that problem, therefore to help that blind is designed and made by time indicator tool with voice output. Generally, the tool's instructions when using RTC DS1307, is microcontroller ATmega16 and ISD 25 120. Information about hour, minute, date, month, and year obtained from DS1307 RTC is accessed using microcontroller ATmega16, then from the data when the information obtained is matched in the voice storage unit on ISD25120. As a results,will be obtained time information data such as voice. Besides, time setting, alarm, battery level indicator, and charge the battery with the sound as well is the tool is equipped permanently. Finally, this tool can help the blind people to be more independent in making it easier to tell the time in living day-to-day activities.


2020 ◽  
Vol 14 (1) ◽  
pp. 34
Author(s):  
Faezah Pardi

This study was conducted at Pulau Jerejak, Penang to determine the floristic variation of its tree communities. A 0.5-hectare study plot was established and divided into 11 subplots. A total of 587 trees with diameter at breast height (DBH) of 5 cm and above were measured, identified and recorded. The tree communities comprised of 84 species, 63 genera and 32 families. The Myrtaceae was the most speciose family with 10 recorded species while Syzgium glaucum (Myrtaceae) was the most frequent species. The Myrtaceae recorded the highest density of 306 individuals while Syzgium glaucum (Myrtaceae) had the highest species density of 182 individuals. Total tree basal area (BA) was 21.47 m2/ha and family with the highest BA was Myrtaceae with 5.81 m2/ha while at species level, Syzgium glaucum (Myrtaceae) was the species with the highest total BA in the plot with value of 4.95 m2/ha. The Shannon˗Weiner Diversity Index of tree communities showed a value of 3.60 (H'max = 4.43) and Evenness Index of 0.81 which indicates high uniformity of tree species. The Margalef Richness Index (R') revealed that the tree species richness was 13.02. Myrtaceae had the highest Importance Value of 20.4%. The Canonical Correspondence Analysis (CCA) showed that Diospyros buxifolia (Ebenaceae) and Pouteria malaccensis (Sapotaceae) were strongly correlated to low pH. Dysoxylum cauliflorum (Meliaceae) and Eriobotrya bengalensis (Rosaceae) were correlated to phosphorus (P) and calcium ion (Ca2+), respectively. Therefore, the trees species composition at Pulau Jerejak showed that the biodiversity is high and conservation action should be implemented to protect endangered tree species. Keywords: Floristic variation; Tree communities; Trees composition; Pulau Jerejak; Species diversity


2020 ◽  
Vol 5 (1) ◽  
pp. 374
Author(s):  
Pauline Jin Wee Mah ◽  
Nur Nadhirah Nanyan

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.


2018 ◽  
Vol 70 (1) ◽  
pp. 103-108
Author(s):  
A.R. Rafidah ◽  
◽  
A.R. Ummul-Nazrah ◽  
M.A. Mohd Hairul ◽  
◽  
...  

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