Kajian Pengendalian Banjir Di Kecamatan Ilir Timur I Palembang

Kota Palembang terletak 100 km dari muara Sungai Musi dan Kota Palembang sangat dominan dipengaruhi oleh pasang surut. Banyak daerah di Palembang dimana tinggi elevasinya berada di bawah elevasi rata-rata muka air laut, sehingga di musim hujan banyak daerah tersebut yang menjadi rawan banjir. Ini diakibatkan oleh pengaruh pasang surut di Sungai Musi. Sebagian besar kawasan di Palembang adalah di daerah depresi, sehingga tanpa sistem drainase yang tepat kawasan yang dikontrol mengalami genangan air yang disebabkan oleh curah hujan.Palembang merupakan kota pariwisata yang memiliki program untuk meningkatkan kinerja sebagai kota aman dan menarik. Sebuah kota tepi pantai yang indah untuk dikunjungi. Oleh karena itu perlu sistem drainase yang terrencana dan terintegrasi agar tidak terjadi banjir ataupun genangan. Maka dari itu diperlukan sistem pengendalian banjir di Kota Palembang dan dalam kajian kami terutama di Kecamatan Ilir Timur I Kota Palembang.Berdasarkan hasil kajian bahwa pengendalian banjir di Kecamatan Ilir Timur I Palembang ini dapat menggunakan sistem drainase. Metode yang dipakai dalam menentukan curah hujan maksimum dengan kala ulang 10 tahun untuk wilayah kecamatan Ilir Timur I adalah Metode Gumbel dan diperoleh R=167,1 mm. Berdasarkan Metode Mononobe didapat nilai intensitas curah hujan maksimum di titik 7-8 yaitu I = 590,3650 mm/jam. Debit air total yang terjadi diwilayah tersebut adalah 230,288 m3/det dengan panjang saluran 23833,54 m

Similarity Based Entropy on Feature Selection for High Dimensional Data Classification

Curse of dimensionality is a major problem in most classification tasks. Feature transformation and feature selection as a feature reduction method can be applied to overcome this problem. Despite of its good performance, feature transformation is not easily interpretable because the physical meaning of the original features cannot be retrieved. On the other side, feature selection with its simple computational process is able to reduce unwanted features and visualize the data to facilitate data understanding. We propose a new feature selection method using similarity based entropy to overcome the high dimensional data problem. Using 6 datasets with high dimensional feature, we have computed the similarity between feature vector and class vector. Then we find the maximum similarity that can be used for calculating the entropy values of each feature. The selected features are features that having higher entropy than mean entropy of overall features. The fuzzy k-NN classifier was implemented to evaluate the selected features. The experiment result shows that proposed method is able to deal with high dimensional data problem with average accuracy of 80.5%

Scattering from supramacromolecular structures

We study theoretically the scattering imprint of a number of branched supramacromolecular architectures, namely, polydisperse stars and dendrimeric, hyperbranched structures. We show that polydispersity and nature of branching highly influence the intermediate wavevector region of the scattering structure factor, thus providing insight into the morphology of different aggregates formed in polymer solutions.Comment: 20 pages, 8 figures To appear in PR

Catalytic Performance of Calcium-Lanthanum co-doped Ceria (Ce0.85-xLa0.15CaxO2-δ) in Partial Oxidation of Methane

In this study, Ce0.85-xLa0.15CaxO2-δ was synthesized using sol-gel combustion method and appliedfor partial oxidation of methane (POM). The physicochemical properties of catalyst were analyzed using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and thermogravimetric analysis (TGA). Material shows a pure cubical structure and is highly stable up to 850 °C. The performance testing indicated the conversion of CH4 is 65% and selectivity of H2 and CO are 28% and 8%, respectively. The performance indicated the catalyst has a potential to be used for partial oxidation of methane on a larger scale. Copyright © 2021 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

The potential use of service-oriented infrastructure framework to enable transparent vertical scalability of cloud computing infrastructure

Cloud computing technology has become familiar to most Internet users. Subsequently, there has been an increased growth in the use of cloud computing, including Infrastructure as a Service (IaaS). To ensure that IaaS can easily meet the growing demand, IaaS providers usually increase the capacity of their facilities in a vertical IaaS increase capability and the capacity for local IaaS amenities such as increasing the number of servers, storage and network bandwidth. However, at the same time, horizontal scalability is sometimes not enough and requires additional strategies to ensure that the large number of IaaS service requests can be met. Therefore, strategies requiring horizontal scalability are more complex than the vertical scalability strategies because they involve the interaction of more than one facility at different service centers. To reduce the complexity of the implementation of the horizontal scalability of the IaaS infrastructures, the use of a technology service oriented infrastructure is recommended to ensure that the interaction between two or more different service centers can be done more simply and easily even though it is likely to involve a wide range of communication technologies and different cloud computing management. This is because the service oriented infrastructure acts as a middle man that translates and processes interactions and protocols of different cloud computing infrastructures without the modification of the complex to ensure horizontal scalability can be run easily and smoothly. This paper presents the potential of using a service-oriented infrastructure framework to enable transparent vertical scalability of cloud computing infrastructures by adapting three projects in this research: SLA@SOI consortium, Open Cloud Computing Interface (OCCI), and OpenStack

Development of lanthanum strontium cobalt ferrite composite cathodes for intermediate- to low-temperature solid oxide fuel cells

Solid oxide fuel cells (SOFCs) offer high energy conversion, low noise, low pollutant emission, and low processing cost. Despite many advantages, SOFCs face a major challenge in competing with other types of fuel cells because of their high operating temperature. The necessity to reduce the operational temperature of SOFCs has led to the development of research into the materials and fabrication technology of fuel cells. The use of composite cathodes significantly reduces the cathode polarization resistance and expands the triple phase boundary area available for oxygen reduction. Powder preparation and composite cathode fabrication also affect the overall performance of composite cathodes and fuel cells. Among many types of cathode materials, lanthanum-based materials such as lanthanum strontium cobalt ferrite (La1-xSrxCo1-yFeyO3-δ) have recently been discovered to offer great compatibility with ceria-based electrolytes in performing as composite cathode materials for intermediate- to low-temperature SOFCs (IT-LTSOFCs). This paper reviews various ceria-based composite cathodes for IT-LTSOFCs and focuses on the aspects of progress and challenges in materials technology