Sriwijaya University

About: Sriwijaya University is a education organization based out in Palembang, Indonesia. It is known for research contribution in the topics: Population & Context (language use). The organization has 5366 authors who have published 5139 publications receiving 15175 citations. The organization is also known as: Universitas Sriwijaya.

Electrode for proton exchange membrane fuel cells: A review

Abstract: The electrode is the key component of the membrane electrode assembly (MEA) of proton exchange membrane fuel cells (PEMFCs). The electrochemical reaction of hydrogen (fuel) and oxygen that transform into water and electrical energy occurs at the catalyst site. Attempts to improve the performance and durability of electrodes have sought to overcome the challenges arising from utilizing PEMFCs as an efficient and competitive energy source. To accomplish this goal and to solve the problems related to using PEMFC electrodes, the structure and function of each component and the manufacturing method must be comprehensively understood, and the electrode performance and durability of the cell must be characterized. Therefore, in this paper, we discuss the components, preparation, functions and performance of the electrodes used in PEMFCs. This review aims to provide comprehensive information regarding PEMFC electrodes.

CICIDS-2017 Dataset Feature Analysis With Information Gain for Anomaly Detection

Abstract: Feature selection (FS) is one of the important tasks of data preprocessing in data analytics. The data with a large number of features will affect the computational complexity, increase a huge amount of resource usage and time consumption for data analytics. The objective of this study is to analyze relevant and significant features of huge network traffic to be used to improve the accuracy of traffic anomaly detection and to decrease its execution time. Information Gain is the most feature selection technique used in Intrusion Detection System (IDS) research. This study uses Information Gain, ranking and grouping the features according to the minimum weight values to select relevant and significant features, and then implements Random Forest (RF), Bayes Net (BN), Random Tree (RT), Naive Bayes (NB) and J48 classifier algorithms in experiments on CICIDS-2017 dataset. The experiment results show that the number of relevant and significant features yielded by Information Gain affects significantly the improvement of detection accuracy and execution time. Specifically, the Random Forest algorithm has the highest accuracy of 99.86% using the relevant selected features of 22, whereas the J48 classifier algorithm provides an accuracy of 99.87% using 52 relevant selected features with longer execution time.

Mitochondrial fission - a drug target for cytoprotection or cytodestruction?

Abstract: Mitochondria are morphologically dynamic organelles constantly undergoing processes of fission and fusion that maintain integrity and bioenergetics of the organelle: these processes are vital for cell survival. Disruption in the balance of mitochondrial fusion and fission is thought to play a role in several pathological conditions including ischemic heart disease. Proteins involved in regulating the processes of mitochondrial fusion and fission are therefore potential targets for pharmacological therapies. Mdivi-1 is a small molecule inhibitor of the mitochondrial fission protein Drp1. Inhibiting mitochondrial fission with Mdivi-1 has proven cytoprotective benefits in several cell types involved in a wide array of cardiovascular injury models. On the other hand, Mdivi-1 can also exert antiproliferative and cytotoxic effects, particularly in hyperproliferative cells. In this review, we discuss these divergent effects of Mdivi-1 on cell survival, as well as the potential and limitations of Mdivi-1 as a therapeutic agent.