Pembuatan Silika High Grade dari Fly Ash Sawit dengan Proses Ekstraksi dan Cation Exchange

One alternative raw materials manufacture of high grade silica is using palm oil mill fly ash. This research aimed to study the effect of temperatureprocess, time and the ratio mass of zeolite and obtain optimum conditions cation exchange process (Fe) in a solution of sodium silicate with raw material palm oil mill fly ash. Palm oil mill fly ash is heated using oven at 105° C for 24 hours. Then fly ash reacted with 1,4N NaOH solution at 105° C for 50 minutes. Then obtained sodium silicate solution is reacted with Na-zeolite. The results of the optimization then precipitated using 10% H2SO4 and derived solidsilica. XRF analysis results showed solid silica has a purity of 96.129%

Factor influences selection of Islamic banking: a study on Malaysian customer preferences

The emergence of strong Islamic movements in last three decades has generated a renewed interest in Islamic economics, especially in Islamic interest free banking. Currently Islamic bank strategically offering high quality products and services to satisfy their customers due to the strong competition, customer expectation for high quality services and rapidly changes of technology. The purpose of this study is to investigate major factors that are reflecting to customers’ perception and satisfaction on Islamic banking. This study hope to analyze and determine the perception, quality of services, availability of services, confidence in bank and social and religious perspective about Islamic banking system. A Logit model is employed to anticipate the effects of the explanatory variables. The analysis confirms the significant positive relationship of quality of services, availability of services, social and religious perspective and confidence in bank with customers’ perception about Islamic bank. These factors are expected to have great role for influencing customer mind. In conclusion, customers can derive a better understanding of the activities that are undertaken by bank and how the way these activities are being dealt with

A Review On Agile Decision Making In Crisis Management

Agility in decision making has a potential to resolve crisis management; therefore a specific agile decision making technique should be implemented in crisis management. Crisis management requires the agility in decision making in order to resolve the crisis. The decision made has to be flexible enough so that the solution can be delivered on time. In having the decision, there are people that will contribute some suggestion, opinion, experience or knowledge. The virtual knowledge sharing is the vital part on delivering the agile decision making. This paper reviews such methods on agile decision making towards crisis management and the relation with virtual knowledge sharing

Enhanced Oxygen Reduction Reaction of LSCF Cathode Material Added with NiO for IT-SOFC

La0.6Sr0.4Co0.2Fe0.8O3-δ (LSCF) is one of the mixed ionic electronic conductors that could be feasibly used in an intermediate temperature solid oxide fuel cell (IT-SOFC). In this study, LSCF and NiO were prepared using a modified Pechini method and calcined at three different temperatures ranging from 600 °C to 900 °C. The prepared LSCF was added with 5% NiO (denoted as LSCF-NiO) as cathode material. The physical and electrical properties of the prepared cathode were investigated. X-ray diffraction data revealed that at calcination temperatures of 600 °C–900 °C, NiO and LSCF maintained their phases and conformed the cubic structure for NiO and orthorhombic structure for LSCF. The calcination temperature showed significant influence on the particle size of the prepared LSCF-NiO, as depicted by scanning electron microscopy (SEM), and all the powders reached a nanoscale size. The SEM cross section of LSCF-NiO layer on gadolinium-doped cerium electrolyte showed an acceptable percentage of cathode porosity and good adhesivity at cathode/electrolyte interface. Energy dispersive X-ray analysis further verified the purity of the samples. Brunauer–Emmett–Teller surface area analysis was conducted, and the results revealed a trend of decreased surface area with an increase in calcining temperature. At an operating temperature of 800 °C, the electrochemical impedance spectroscopic results showed that LSCF-NiO 800 had a low Rp of 0.07 Ω cm2, and its Ea was found to be 159.5 kJ/mol, indicating that LSCF-NiO 800 is fit to be used as cathode material in IT-SOFC application

Recent Progress in Lipid Nanoparticles for Cancer Theranostics: Opportunity and Challenges

Cancer is one of the major leading causes of mortality in the world. The implication of nanotherapeutics in cancer has garnered splendid attention owing to their capability to efficiently address various difficulties associated with conventional drug delivery systems such as non-specific biodistribution, poor efficacy, and the possibility of occurrence of multi-drug resistance. Amongst a plethora of nanocarriers for drugs, this review emphasized lipidic nanocarrier systems for delivering anticancer therapeutics because of their biocompatibility, safety, high drug loading and capability to simultaneously carrying imaging agent and ligands as well. Furthermore, to date, the lack of interaction between diagnosis and treatment has hampered the efforts of the nanotherapeutic approach alone to deal with cancer effectively. Therefore, a novel paradigm with concomitant imaging (with contrasting agents), targeting (with biomarkers), and anticancer agent being delivered in one lipidic nanocarrier system (as cancer theranostics) seems to be very promising in overcoming various hurdles in effective cancer treatment. The major obstacles that are supposed to be addressed by employing lipidic theranostic nanomedicine include nanomedicine reach to tumor cells, drug internalization in cancer cells for therapeutic intervention, off-site drug distribution, and uptake via the host immune system. A comprehensive account of recent research updates in the field of lipidic nanocarrier loaded with therapeutic and diagnostic agents is covered in the present article. Nevertheless, there are notable hurdles in the clinical translation of the lipidic theranostic nanomedicines, which are also highlighted in the present review along with plausible countermeasures.Peer reviewedFinal Published versio

Failure of steel helical gear used for automotive transmission

The advantage of helical gear that can operate silently, on parallel and nonparallel shafts at high capacity has been great such that helical gears are used in almost all car transmission systems. As such, study on two major failures of helical gears which are due to bending and contact stresses is critical. In this research, modelling of a helical gear that is used in a 5-speed transmission car system has been conducted using finite element method. Bending and pitting stress analysis have been conducted on this helical gear that was modelled in 3D involute form. The obtained results of maximum bending and contact stresses have been compared to analytical results obtained using the American Gear Manufacturing Association (AGMA) formulations. The results of the FEM modelling and the AGMA formulations have been found to be in good agreement. Furthermore, parametric studies have been conducted on the effects of face width and helical angle of the gears on the bending and pitting stresses. It is observed that the increase of face width of the gear will decrease the maximum bending stress while the increase of the helical angle will increase the pitting stress in a non-linear fashion for both cases

Identification of masses in digital mammogram using gray level co-occurrence matrices

Digital mammogram has become the most effective technique for early breast cancer detection modality. Digital mammogram takes an electronic image of the breast and stores it directly in a computer. The aim of this study is to develop an automated system for assisting the analysis of digital mammograms. Computer image processing techniques will be applied to enhance images and this is followed by segmentation of the region of interest (ROI). Subsequently, the textural features will be extracted from the ROI. The texture features will be used to classify the ROIs as either masses or non-masses. In this study normal breast images and breast image with masses used as the standard input to the proposed system are taken from Mammographic Image Analysis Society (MIAS) digital mammogram database. In MIAS database, masses are grouped into either spiculated, circumscribed or ill-defined. Additional information includes location of masses centres and radius of masses. The extraction of the textural features of ROIs is done by using gray level co-occurrence matrices (GLCM) which is constructed at four different directions for each ROI. The results show that the GLCM at 0º, 45º, 90º and 135º with a block size of 8X8 give significant texture information to identify between masses and non-masses tissues. Analysis of GLCM properties i.e. contrast, energy and homogeneity resulted in receiver operating characteristics (ROC) curve area of Az = 0.84 for Otsu’s method, 0.82 for thresholding method and Az = 0.7 for K-mean clustering. ROC curve area of 0.8-0.9 is rated as good results. The authors’ proposed method contains no complicated algorithm. The detection is based on a decision tree with five criterions to be analysed. This simplicity leads to less computational time. Thus, this approach is suitable for automated real-time breast cancer diagnosis system

Infant birth weight estimation and low birth weight classification in United Arab Emirates using machine learning algorithms

Accurate prediction of a newborn’s birth weight (BW) is a crucial determinant to evaluate the newborn’s health and safety. Infants with low BW (LBW) are at a higher risk of serious short- and long-term health outcomes. Over the past decade, machine learning (ML) techniques have shown a successful breakthrough in the field of medical diagnostics. Various automated systems have been proposed that use maternal features for LBW prediction. However, each proposed system uses different maternal features for LBW classification and estimation. Therefore, this paper provides a detailed setup for BW estimation and LBW classification. Multiple subsets of features were combined to perform predictions with and without feature selection techniques. Furthermore, the synthetic minority oversampling technique was employed to oversample the minority class. The performance of 30 ML algorithms was evaluated for both infant BW estimation and LBW classification. Experiments were performed on a self-created dataset with 88 features. The dataset was obtained from 821 women from three hospitals in the United Arab Emirates. Different performance metrics, such as mean absolute error and mean absolute percent error, were used for BW estimation. Accuracy, precision, recall, F-scores, and confusion matrices were used for LBW classification. Extensive experiments performed using five-folds cross validation show that the best weight estimation was obtained using Random Forest algorithm with mean absolute error of 294.53 g while the best classification performance was obtained using Logistic Regression with SMOTE oversampling techniques that achieved accuracy, precision, recall and F1 score of 90.24%, 87.6%, 90.2% and 0.89, respectively. The results also suggest that features such as diabetes, hypertension, and gestational age, play a vital role in LBW classification.</p