Scientific Computing Environment Research Articles

Co-seismic Ground Deformation Monitoring on Brebes-Segment of Baribis-Kendeng Fault Zone Based on Sentinel-1 Data

Co-seismic deformation is a sudden change in the earth’s surface in a fault zone. Therefore, with modern satellite imagery, it is possible to investigate. Synthetic Aperture Radar (SAR) data from Mission Sentinel-1 is one example of satellite imagery that can be used to identify deformation. We employ the interferometry method by utilizing the Interferometric synthetic aperture radar Scientific Computing Environment (ISCE) and another InSAR software to monitor the co-seismic ground deformation in the form of line-of-sight (LOS) displacement. This research focused on the Brebes Segment of the Baribis-Kendeng Fault Zone and applied the interferometry method for the March 22, 2015, Balapulang earthquake (M4.7) and December 11, 2020, Brebes earthquake (M4.2). The earthquake event choice is based on the shallow depth of the hypocenter, which represents the earthquake originating from the fault in the crustal, not the megathrust subduction. The results show that despite the earthquake occurring under the thick quaternary sediment of the north shore of Java Island, the deformation caused by the co-seismic is still emerging to the surface. The LOS displacement was detected within the range of 6 cm from the ascending and descending track of the satellite sensors. Furthermore, this result may provide new information on the Baribis-Kendeng Fault zone, specifically the Brebes Segment.

Country-scale assessment of urban areas, population, and households exposed to land subsidence using Sentinel-1 InSAR, and GPS time series

The increased need for water resources in urban sprawls and intense droughts has forced more aggressive groundwater extraction resulting in numerous urban areas undergoing land subsidence. In most cases, only some large metropolitan areas have been well-characterized for subsidence. However, there is no existing country-wide assessment of urban areas, population, and households exposed to this process. This research showcases a methodology to systematically evaluate urban localities with land subsidence higher than − 2.8 cm/year throughout Mexico. We used Interferometric Synthetic Aperture Radar (InSAR) tools with a dataset of 4611 scenes from European Space Agency’s Sentinel-1 A/B SAR sensors acquired from descending orbits from September 2018 through October 2019. This dataset was processed at a supercomputer using InSAR Scientific Computing Environment and the Miami InSAR Time Series software in Python software. The quality and calibration of the resulting velocity maps are assessed through a large-scale comparison with observations from 100 continuous GPS sites throughout Mexico. Our results show that an urban area of 3797 km2, 6.9 million households, and 17% of the total population in Mexico is exposed to subsidence velocities of faster than − 2.8 cm/year, in more than 853 urban localities within 29 land subsidence regions. We also confirm previous global potential estimations of subsidence occurrence in low relief areas over unconsolidated deposits and where groundwater aquifers are under stress. The presented research demonstrates the capabilities for surveying urban areas exposed to land subsidence at a country-scale level by combining Sentinel-1 velocities with spatial national census data.

Method for Assemblage of an Open Access Data Set for Research in Geomagnetic Effects on GPS/GNSS Ionospheric Delay in Sub-equatorial Regions

Space weather, geomagnetic, and ionospheric effects are major sources of Global Navigation Satellite System’s (GNSS) Positioning, Navigation, and Timing (PNT) service degradation. Researchers studying the problem often face an obstacle in missing large data sets comprising ionospheric effects variables and space weather ones for their studies. Here a formal assemblage method is proposed for data set assemblage for GNSS ionospheric effects assessment that utilises experimental sets of space weather/geomagnetic observations, and raw GNSS pseudorange observations polluted with uncorrected ionospheric delay effects to estimate Total Electron Content (TEC) as a target variable outlining the ionospheric effects on GNSS. The five Observations Quality Principles (OQP) are proposed for the observations to be used in statistical learning model development to comply to. The proposed assemblage method is demonstrated in a particular case study of an assembled data set for Darwin, NT, Australia, in sub-equatorial zone, using a tailored software developed in the R environment for scientific computing, and a freely available TEC estimation software. The assembled massive data obtained in the demonstration of the proposed method is provided in the open-access manner in support of the international scientific community.

Resource Profiling and Performance Modeling for Distributed Scientific Computing Environments

Scientific applications often require substantial amount of computing resources for running challenging jobs potentially consisting of many tasks from hundreds of thousands to even millions. As a result, many institutions collaborate to solve large-scale problems by creating virtual organizations (VOs), and integrate hundreds of thousands of geographically distributed heterogeneous computing resources. Over the past decade, VOs have been proven to be a powerful research testbed for accessing massive amount of computing resources shared by several organizations at almost no cost. However, VOs often suffer from providing exact dynamic resource information due to their scale and autonomous resource management policies. Furthermore, shared resources are inconsistent, making it difficult to accurately forecast resource capacity. An effective VO’s resource profiling and modeling system can address these problems by forecasting resource characteristics and availability. This paper presents effective resource profiling and performance prediction models including Adaptive Filter-based Online Linear Regression (AFOLR) and Adaptive Filter-based Moving Average (AFMV) based on the linear difference equation combining past predicted values and recent profiled information, which aim to support large-scale applications in distributed scientific computing environments. We performed quantitative analysis and conducted microbenchmark experiments on a real multinational shared computing platform. Our evaluation results demonstrate that the proposed prediction schemes outperform well-known common approaches in terms of accuracy, and actually can help users in a shared resource environment to run their large-scale applications by effectively forecasting various computing resource capacity and performance.

Crustal Deformation of the Kendeng Fault Branches Area from GNSS and InSAR Data in Surabaya City, Indonesia

Slip rates on active faults derived from the interseismic velocity field are critical to understanding seismic hazards in metropolitan cities. This study integrated the data from the Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) to evaluate the interseismic velocities in the second-largest city in Indonesia, Surabaya, where branches of the Kendeng fault (the Surabaya and the Waru faults) pass through. Data from 16 campaign-mode GNSS stations collected between 2017 and 2020 from previous research are reprocessed to estimate the velocity field. Horizontal velocities under the ITRF frame range between -23.8 mm/yr and 47.9 mm/yr toward the southeast. Vertical velocities generally range between -1.3 mm/yr and -112.2 mm/yr. Sentinel-1A SAR data of both ascending and descending tracks acquired between November 2014 and July 2020 were used to generate the interferograms with the InSAR Scientific Computing Environment (ISCE) software. Furthermore, cumulative displacement time series were constructed using the Small BAseline Subset (SBAS) technique within the Generic InSAR Analysis Toolbox (GIAnT). This study also carried out the detection of outlier SAR epochs to improve the precision of Line-of-sight (LOS) velocity estimates. The LOS velocities range from -14.8 to 10.8 mm/yr in the ascending track and from -12.7 to 9.5 mm/yr in the descending track. These results will facilitate the detection of coupling behaviors on the Kendeng fault branches, which can improve our understanding of seismic risks in the Surabaya area.

A South Pacific Cyclone-caused GPS Positioning Error and Its Impact on Remote Oceanic Island Communities

Satellite navigation gains importance in sustainable development of modern civilisation. With the increasing number of GNSS-based technology and socio-economic systems and services, satellite navigation has become an essential component of national infrastructure. This calls for novel requirements on GNSS positioning perfomance, and increasing need for resilient GNSS development. Here we examined the impact of rapidly developing tropical cyclone on GPS positioning performance degradation, and the resulting impact on oceanic non-navigation and navigation GPS applications. We presented the methodology for indirect simulation-based GPS positioning performance evaluation through utilisation of experimental GPS observations, GNSS Software- Defined Radio (SDR) receiver, and a statistical analysis and framework we developed in the R environment for scientific computing. We identified alteration of GPS positioning error components time series statistical properties, and discuss the potential impact on GPS-based services essential for remote oceanic island communities. Manuscript concludes with the summary of findings, proposal for recommendations on improved GNSS resilience, and an outline for future research.

P-02 科学計算環境MATLABを用いた情報通信実習の教材試作

P-02 科学計算環境MATLABを用いた情報通信実習の教材試作

Diagnosis of Distributed Denial of Service Attacks using the Combination Method of Fuzzy Neural Network and Evolutionary Algorithm

Availability, integrity and confidentiality are the key concepts of cyber security. Distributed denial of service attacks affecting the availability of information sources. This type of attack when be successful which led to the non-availability to the information sources. The success and impact of service denial attacks will be identified based on the victims and the risk level, threat and consequences of this attack, according to each case is different. The aim of this study is DDOS attack detection with differential evolutionary algorithm combination method and the fuzzy neural network ANFIS. For this purpose will pay to simulate and evaluate the proposed approach. In order to simulate in this research which is used MATLAB 2013b software which is a programming language and environment for scientific computing. The result of comparison showed that the ANFIS combination algorithm and differential evolution than to the ANFIS algorithm has more accuracy.

Uncertainty Management in Computer Assisted Problem Solving Environment (PSE) for Scientific Computing

Uncertainty Management in Computer Assisted Problem Solving Environment (PSE) for Scientific Computing

A software development environment for Grid computing

AbstractGrid computing has become a popular concept in the last few years. While in the beginning the driving force was metacomputing, the focus has now shifted towards resource management issues and concepts like ubiquitous computing. For the High‐Performance Computing Center Stuttgart (HLRS) the key challenges of Grid computing have come from the demands of its users and customers. With high‐speed networks in place, programmers expect to be able to exploit the overall performance of several instruments and high‐speed systems for their applications. In order to meet these demands, HLRS has set out a research effort to provide these users with the necessary tools to develop and run their codes on clusters of supercomputers. This has resulted in the development of a basic Grid‐computing environment for technical and scientific computing. In this paper we describe the building blocks of this software development environment and focus specifically on communication and debugging. We present the Grid‐enabled MPI implementation PACX‐MPI and the MPI debugger MARMOT. Copyright © 2002 John Wiley & Sons, Ltd.

Distributed computing: new power for scientific visualization

Distributed computing provides unique benefits for scientific visualization in this system (Discover) that supports interactive visualization and cooperative work for nonprogrammers. Discover (Distributed Interactive Scientific Computing and Visualization Environment), is suitable for many areas, but we have concentrated on medical image analysis and generation-one of the the most rapidly growing applications for scientific visualization. In its present form, Discover acts as a framework for clinical applications. True to its name, it allows a variety of users to discover the relevant information in a vast body of scientific data. Nonprogrammers, such as physicians and radiologists, interactively display and manipulate the two and three dimensional medical objects, visualize the results, control system computation, and generally drive the image analysis process. The emphasis is on the distributed nature of the software architecture and its functions. We also describe a unique load balancing algorithm designed to maximize workstation performance.

A distributed and interactive three-dimensional medical image system

Three-dimensional (3D) arrays of digital data representing spatial volumes arise in many scientific applications, such as computed tomography (CT) and magnetic resonance imaging (MRI) created by imaging a series of cross sections of human bodies in medical applications. In this article, a software system architecture, called DISCOVER (a Distributed Interactive Scientific Computing and Visualization EnviRonment), which can take advantage of the power of parallel processing, is proposed and implemented for interactive visualization and manipulation of the 3D digital data. The surface-rendering and the volume-rendering algorithms are implemented. The same software program can be executed on several different hardware platforms. We also propose a new rendering algorithm, called volume-surface rendering, for medical applications. The algorithm enables users to visualize the external and internal structures of medical objects simultaneously. The network version of the DISCOVER, as it stands today, is in practical use in the Hospital of National Cheng Kung University in Taiwan for real clinical applications.

Object-oriented visualization of scientific data

Scene (Scientific Computing Environment for Numerical Experimentation) is a scientific/engineering user interface which implements object-oriented paradigms in a distributed system of facilities. The user interface and control elements are implemented in Smalltalk and the numerically intensive work, both for model computation and graphics manipulations, are done in C as: (1) 'user primitives' (subroutines written in C and lined into the Smalltalk image on the workstation); and/or (2) as system calls to remote processes (programs written in C, FORTRAN, etc.) running on 'black end' computers (e.g. an Ardent Titan, a BBN Butterfly, or a NCUBE/ten hypercube). The present structure of the object-oriented graphical functions and the distributed process implementation is described. An example of an object-oriented computational data base running as a back end process and subject to interactive visual and quantitative queries is presented.

The Personal Scientific Computing Environment A New Approach to Power Industry Computer Applications

The Personal Scientific Computing Environment A New Approach to Power Industry Computer Applications

The Personal Scientific Computing Environment: A New Approach to Power Industry Computer Applications

Another revolution is occurring in computer hardware that will affect computer users in the power industry. The first generation of powerful personal1 computers for scientific applications is now on the market. These computers have several advantages over conventional computers: very fast graphics, uniform response time, and a visually-oriente user environment that increases user productivity dramatically. These advantages are the result of having a very powerful processor devoted to a single user's needs.