Disaster management system: Providing an effective communication mechanism and accessible data analysis in Ghana

Applied project submitted to the Department of Computer Science, Ashesi University, in partial fulfillment of Bachelor of Science degree in Computer Science, April 2018Disaster is an unfortunate, yet common phenomenon in our world today. This phenomenon stakes undesirable claims on lives, infrastructure and services alike. Those affected both directly and indirectly must overcome challenges, not only during but also, after the occurrence of disasters. Imperatively, it is always prefered to be better equipped to prevent the disaster and avoid it altogether. Yet that is impossible as not all disasters are man-made. Disaster management then must be up to the task to reduce consequences to the barest minimum. This has not been the case in Ghana. There is a great need for efficient communication channels and accessible data that will greatly help to preserve lives and property in the country. This project focuses directly on meeting this need. This paper outlines the various technologies and processes employed in developing a disaster management system that has great potential in solving the said problem. The application is an Android application with a simple and intuitive design. Challenges encountered in the development process are also discussed. In addition, suggestions on future work on this application are also given.Ashesi Universit

Bot-Based Emergency Software Applications for Natural Disaster Situations

Upon a serious emergency situation such as a natural disaster, people quickly try to call their friends and family with the software they use every day. On the other hand, people also tend to participate as a volunteer for rescue purposes. It is unlikely and impractical for these people to download and learn to use an application specially designed for aid processes. In this work, we investigate the feasibility of including bots, which provide a mechanism to get inside the software that people use daily, to develop emergency software applications designed to be used by victims and volunteers during stressful situations. In such situations, it is necessary to achieve efficiency, scalability, fault tolerance, elasticity, and mobility between data centers. We evaluate three bot-based applications. The first one, named Jayma, sends information about affected people during the natural disaster to a network of contacts. The second bot-based application, Ayni, manages and assigns tasks to volunteers. The third bot-based application named Rimay registers volunteers and manages campaigns and emergency tasks. The applications are built using common practice for distributed software architecture design. Most of the components forming the architecture are from existing public domain software, and some components are even consumed as an external service as in the case of Telegram. Moreover, the applications are executed on commodity hardware usually available from universities. We evaluate the applications to detect critical tasks, bottlenecks, and the most critical resource. Results show that Ayni and Rimay tend to saturate the CPU faster than other resources. Meanwhile, the RAM memory tends to reach the highest utilization level in the Jayma application.Fil: Ovando Leon, Gabriel. Universidad de Santiago de Chile; ChileFil: Veas Castillo, Luis. Universidad de Santiago de Chile; ChileFil: Gil Costa, Graciela Verónica. Universidad Nacional de San Luis; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis; ArgentinaFil: Marin, Mauricio. Universidad de Santiago de Chile; Chil

A taxonomy and business analysis for mobile web applications

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2009.Includes bibliographical references (p. 113-115).Mobile web applications refer to web applications on mobile devices, aimed at personalizing, integrating, and discovering mobile contents in user contexts. This thesis presents a comprehensive study of mobile web applications by proposing a new taxonomy for mobile web applications, and conducting a business analysis in the field of mobile web applications. The thesis reviews the current surrounding environment for mobile web applications, namely, web 2.0 and 3.0, wireless communication technology, and Smartphone platform. The recent entry and success of Apple's iPhone greatly enhanced the public awareness of the Smartphone technology. Google's release of open-source Android platform and T-Mobile's deployment of Android-powered "Dream" Smartphone not only intensify the competition among suppliers, but also provide an open-source foundation for mobile web applications. This thesis introduces a new mobile web application taxonomy to systematically study the values and the groupings of the mobile web applications. By introducing features and categories, the taxonomy provides a framework so the related companies and businesses can be comparatively analyzed and summarized. Selected case companies are studied in the light of the taxonomy. The thesis discusses the key issues of mobile web aggregation, namely, mobile application development platform, context modeling, mobile user interface, mobile application logic, and mobile web aggregation strategy.(cont.) "System Thinking" is applied to the management of mobile web application business. The market ecosystem, the value proposition, and the revenue model for mobile web application are described. A system dynamic model is constructed to understand the dynamic among the key factors in the mobile web business. Experimental results are reported in the thesis.by Kevin Hao Liu.S.M

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

GIS in Healthcare

The landscape of healthcare is dynamic, gradually becoming more complicated with factors beyond simple supply and demand. Similar to the diversity of social, political and economic contexts, the practical utilization of healthcare resources also varies around the world. However, the spatial components of these contexts, along with aspects of supply and demand, can reveal a common theme among these factors. This book presents advancements in GIS applications that reveal the complexity of and solutions for a dynamic healthcare landscape