Preparation Polyelectrolyte Complexes of Chitosan-Polyacrylic Acid-Modified Iron Sand Leachate for Proton Exchange Membranes

ABSTRACT

Polyelectrolyte complex (PEC) of chitosan (Chi) and poly (acrylic acid) (PAA)-modified iron sand leachate were prepared and considered for applicability as a proton exchange membrane in fuel cells. Chi-PAA-hematite blended in different weight ratios and the resulting membranes were treated to enable the formation of the polyelectrolyte. The membranes of Chi-PAA polyblend were treated using iron sand leachate and reveal high ion exchange capacity (IEC), proton conductivity, water uptake, and good mechanical stability. The result of research indicated that the membrane with 40 wt% of Chi and 60 wt% of PAA blend which its conductivity of 6.10 × 10^?2 S cm^?1 was potentially for a proton exchange membrane in fuel cell applications.     

Suction-based Grasp Point Estimation in Cluttered Environment for Robotic Manipulator Using Deep Learning-based Affordance Map

Machine Intelligence Research - Perception and manipulation tasks for robotic manipulators involving highly-cluttered objects have become increasingly in-demand for achieving a more efficient...     

A novel intrusion detection system based on hierarchical clustering and support vector machines

This study proposed an SVM-based intrusion detection system, which combines a hierarchical clustering algorithm, a simple feature selection procedure, and the SVM technique. The hierarchical clustering algorithm provided the SVM with fewer, abstracted, and higher-qualified training instances that are derived from the KDD Cup 1999 training set. It was able to greatly shorten the training time, but also improve the performance of resultant SVM. The simple feature selection procedure was applied to eliminate unimportant features from the training set so the obtained SVM model could classify the network traffic data more accurately. The famous KDD Cup 1999 dataset was used to evaluate the proposed system. Compared with other intrusion detection systems that are based on the same dataset, this system showed better performance in the detection of DoS and Probe attacks, and the beset performance in overall accuracy.     

Fuzzy geographically weighted clustering using artificial bee colony: An efficient geo-demographic analysis algorithm and applications to the analysis of crime behavior in population

Geo-demographic analysis is an essential part of a geographical information system (GIS) for predicting people’s behavior based on statistical models and their residential location. Fuzzy Geographically Weighted Clustering (FGWC) serves as one of the most efficient algorithms in geo-demographic analysis. Despite being an effective algorithm, FGWC is sensitive to initialize when the random selection of cluster centers makes the iterative process falling into the local optimal solution easily. Artificial Bee Colony (ABC), one of the most popular meta-heuristic algorithms, can be regarded as the tool to achieve global optimization solutions. This research aims to propose a novel geo-demographic analysis algorithm that integrates FGWC to the optimization scheme of ABC for improving geo-demographic clustering accuracy. Experimental results on various datasets show that the clustering quality of the proposed algorithm called FGWC-ABC is better than those of other relevant methods. The proposed algorithm is also applied to a decision-making application for analyzing crime behavior problem in the population using the US communities and crime dataset. It provides fuzzy rules to determine the violent crime rate in terms of linguistic labels from socioeconomic variables. These results are significant to make predictions of further US violent crime rate and to facilitate appropriate decisions on prevention such the situations in the future.     

Screening for lipid depositor of Indonesian microalgae isolated from seashore and peat-land

The screening for finding the lipid producer of indigenous Indonesian tropical microalgae that obtained from peat-land at Riau, Sumatra and seashore at Lombok has carried out. Preliminary screening was done by selection on faster growing algae from 44 (forty-four) isolates. 10 (ten) isolates were chosen for further analysis. Out of 10 selected isolates shows that five isolates have indication rapid growth and high content of lipid, furthermore those chose isolates were observed comprehensively, namely LIPI11-2-Al005, LIPI11-2-Al010, LIPI11-2-Al015, LIPI11-2-Al018, and LIPI11-2-Al019. The microalgae are belong to the eukaryotic microalgae and its seem to be closed to Chlorophytes that has cell nuclear with an envelope, light green chloroplast, thick cell wall, round and elongated cell features. Cultivation of the microalgae in laboratory condition (1 L) has shown that lipid content was about 20–35% base in cell dry weight. The highest lipid content was found in the isolate LIPI11-2-Al018 of 30.74% per dry weight cell. LIPI11-2-A1018 therefore was test for scale up cultivation reach the culture volume of 5 L in the cylindrical photobioreactor, and expected to be source of triglycerides and lipids for biodiesel ingredient.     

The influence of calcination temperature on catalytic activities in a Co based catalyst for CO2 dry reforming

The carbon dioxide dry reforming of methane (CDR) reaction could be thermodynamically favored in the range of 800 to 1,000 °C. However, the catalyst in this reaction should be avoided at the calcination temperature over 800 °C since strong metal support interaction (SMSI) in this temperature range can decrease activity due to loss of active sites. Therefore, we focused on optimizing the temperature of pretreatment and a comparison of surface characterization results for CDR. Results related to metal sintering over support, re-dispersion by changing of particle size of metal-support, and strong metal support interaction were observed and confirmed in this work. In our conclusion, optimum calcination temperature for a preparation of catalyst was proposed that 400 °C showed a higher and more stable catalytic activity without changing of support characteristics.     

The nature of polymer grafts and substrate shape on the surface degradation of poly(l‐lactide)

Surface grafting of functional polymers is an effective method to alter material properties and degradation behavior. Two different substrate shapes of poly(l ‐lactide) (PLLA), i.e., films and microparticles, were surface‐grafted with hydrophilic monomers, and their surface degradation was monitored. Surface grafting with a hydrophilic and acidic polymer graft [acrylic acid (AA)] induced large alterations in the surface morphology and topography of the films. In contrast, hydrophilic and neutral polymer grafts [acrylamide (AAm)] had no significant effect on the surface degradation behavior, while the PLLA reference and co‐monomeric (AA/AAm) polymer‐grafted samples exhibited intermediate surface degradation rates. The grafted PAA chains induced a local acidic environment on the surface of the substrates, which in turn catalyzed the surface degradation process. This effect was more pronounced in the films than in the microparticles. Thus, the nature of the grafted chains and substrate geometry were shown to affect the surface degradation behavior of PLLA substrates. © 2015 The Authors Journal of Applied Polymer Science Published by Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42736.     

Validation and improvement of gamma heating calculation methods for the G.A. Siwabessy multipurpose reactor

Nuclear Science and Techniques - This study presents the RF design of a linear accelerator (linac) operated in single-bunch mode. The accelerator is powered by a compressed RF pulse produced from a...