Basic finance made accessible in Excel 2007 : "the big 5, plus 2"

The basic principles and equations are developed for elementary finance, based on the concept of compound interest. The five quantities of interest in such problems are present value, future value, amount of periodic payment, number of periods and the rate of interest per period. We consider three distinct means of computing each of these five quantities in Excel 2007: (i) use of algebraic equations, (ii) by recursive schedule and the Goal Seek facility, and (iii) use of Excel's intrinsic financial functions. The paper is intended to be used as the basis for a lesson plan and contains many examples and solved problems. Comment is made regarding the relative difficulty of each approach, and a prominent theme is the systematic use of more than one method to increase student understanding and build confidence in the answer obtained. Full instructions to build each type of model are given and a complete set of examples and solutions may be downloaded (Examples.xlsx and Solutions.xlsx).

The big blue

For the 1.5 million travellers who annually visit the Blue Mountains to experience the Australian Bush, it just got closer. The Echo Point redevelopment by Tract Consultants is a megastructure in the void.

A news story as big as a doctoral thesis? : deploying journalistic methodology in academic research

The purpose of this paper is to identify and recommend the emergence of an academic research methodology for Journalism the academic discipline, through reviewing various journalistic methods of research – those making up a key element in such methodology. Its focus is on journalistic styles of work employed in academic contexts especially research on mass media issues. It proposes that channelling such activity into disciplined academic forms will enhance both: allowing the former to provide more durable and deeper outcomes, injecting additional energy and intensity of purpose into the latter. It will briefly consider characteristics of research methodologies and methods, generally; characteristics of the Journalism discipline, and its relationship with mass media industries and professions. The model of journalism used here is the Western liberal stream. A proposition is made, that teaching and research in universities focused on professional preparation of journalists, has developed so that it is a mature academic discipline. Its adherents are for the most part academics with background in journalistic practice, and so able to deploy intellectual skills of journalists, while also accredited with Higher Degrees principally in humanities. Research produced in this discipline area stands to show two characteristics: (a) it employs practices used generally in academic research, e.g. qualitative research methods such as ethnographic studies or participant observation, or review of documents including archived media products, and (b) within such contexts it may use more specifically journalistic techniques, e.g. interviewing styles, reflection on practice of journalism, and in creative practice research, journalistic forms of writing – highlighting journalistic / practitioner capabilities of the author. So the Journalism discipline, as a discipline closely allied to a working profession, is described as one where individual professional skills and background preparation for media work will be applicable to academic research. In this connection the core modus operandi will be the directly research-related practices of: insistent establishment of facts, adept crafting of reportage, and economising well with time. Prospective fields for continuing research are described:- work in new media; closer investigation of relations among media producers and audiences; journalism as creative practice, and general publishing by journalists, e.g. writing histories.

Faster than the speed of print : reconciling ‘big data’ social media analysis and academic scholarship

The promise of ‘big data’ has generated a significant deal of interest in the development of new approaches to research in the humanities and social sciences, as well as a range of important critical interventions which warn of an unquestioned rush to ‘big data’. Drawing on the experiences made in developing innovative ‘big data’ approaches to social media research, this paper examines some of the repercussions for the scholarly research and publication practices of those researchers who do pursue the path of ‘big data’–centric investigation in their work. As researchers import the tools and methods of highly quantitative, statistical analysis from the ‘hard’ sciences into computational, digital humanities research, must they also subscribe to the language and assumptions underlying such ‘scientificity’? If so, how does this affect the choices made in gathering, processing, analysing, and disseminating the outcomes of digital humanities research? In particular, is there a need to rethink the forms and formats of publishing scholarly work in order to enable the rigorous scrutiny and replicability of research outcomes?

Rapid scanning of spectrograms for efficient identification of bioacoustic events in big data

Acoustic sensing is a promising approach to scaling faunal biodiversity monitoring. Scaling the analysis of audio collected by acoustic sensors is a big data problem. Standard approaches for dealing with big acoustic data include automated recognition and crowd based analysis. Automatic methods are fast at processing but hard to rigorously design, whilst manual methods are accurate but slow at processing. In particular, manual methods of acoustic data analysis are constrained by a 1:1 time relationship between the data and its analysts. This constraint is the inherent need to listen to the audio data. This paper demonstrates how the efficiency of crowd sourced sound analysis can be increased by an order of magnitude through the visual inspection of audio visualized as spectrograms. Experimental data suggests that an analysis speedup of 12× is obtainable for suitable types of acoustic analysis, given that only spectrograms are shown.

Design Minds The Big Picture Toolkit

The Design Minds The Big Picture Toolkit was one of six K7-12 secondary school design toolkits commissioned by the State Library of Queensland (SLQ) Asia Pacific Design Library (APDL), to facilitate the delivery of the Stage 1 launch of its Design Minds online platform (www.designminds.org.au) partnership initiative with Queensland Government Arts Queensland and the Smithsonian Cooper-Hewitt National Design Museum, on June 29, 2012. Design Minds toolkits are practical guides, underpinned by a combination of one to three of the Design Minds model phases of ‘Inquire’, ‘Ideate’ and ‘Implement’ (supported by at each stage with structured reflection), to enhance existing school curriculum and empower students with real life design exercises, within the classroom environment. Toolkits directly identify links to Naplan, National Curriculum, C2C and Professional Standards benchmarks, as well as the student capabilities of successful and creative 21st century citizens they seek to engender through design thinking. Inspired by the Unlimited: Designing for the Asia Pacific Generation Workshop 2010 (http://eprints.qut.edu.au/47762/), this toolkit explores, through three distinct exercises, ‘design for the other 90%’, addressing tools and approaches to diverse and changing social, cultural, technological and environmental challenges. The Design Minds The Big Picture Toolkit challenges students to be active agents for change and to think creatively and optimistically about solutions to future global issues that deliver social, economic and environmental benefits. More generally, it aims to facilitate awareness in young people, of the role of design in society and the value of design thinking skills in generating strategies to solve basic to complex systemic challenges, as well as to inspire post-secondary pathways and idea generation for education. The toolkit encourages students and teachers to develop sketching, making, communication, presentation and collaboration skills to improve their design process, as well as explore further inquiry (background research) to enhance the ideation exercises. Exercise 1 focuses on the ‘Inquire’ phase, Exercise 2 the ‘Inquire’ and ‘Ideate’ phases, and Exercise 3 concentrates on the ‘Implement’ phase. Depending on the intensity of the focus, the unit of work could be developed over a 4-5 week program (approximately 4-6 x 60 minute lessons/workshops) or as smaller workshops treated as discrete learning experiences. The toolkit is available for public download from http://designminds.org.au/the-big-picture/ on the Design Minds website.

The unfinished revolution : what is missing from the E&P industry’s move to “big data”

One cannot help but be impressed by the inroads that digital oilfield technologies have made into the exploration and production (E&P) industry in the past decade. Today’s production systems can be monitored by “smart” sensors that allow engineers to observe almost any aspect of performance in real time. Our understanding of how reservoirs are behaving has improved considerably since the dawn of this revolution, and the industry has been able to move away from point answers to more holistic “big picture” integrated solutions. Indeed, the industry has already reaped the rewards of many of these kinds of investments. Many billions of dollars of value have been delivered by this heightened awareness of what is going on within our assets and the world around them (Van Den Berg et al. 2010).

Do you have a big stick?

Can I write across media? Yes and no. No, I can’t begin writing a sentence with a pen on paper and then use that pen to write on a screen. I have to change my tools. But, I can use those different tools to write a story that begins in paper and ends on the screen. At it most fundamental level, this is transmedia. Transmedia is not synonymous with digital media as it often involves both digital and nondigital media. A transmedia writer is also not synonymous with writers who write both screenplays and novels. Instead, transmedia often involves the continuation of a story across media.

Practical analysis of big acoustic sensor data for environmental monitoring

Monitoring the environment with acoustic sensors is an effective method for understanding changes in ecosystems. Through extensive monitoring, large-scale, ecologically relevant, datasets can be produced that can inform environmental policy. The collection of acoustic sensor data is a solved problem; the current challenge is the management and analysis of raw audio data to produce useful datasets for ecologists. This paper presents the applied research we use to analyze big acoustic datasets. Its core contribution is the presentation of practical large-scale acoustic data analysis methodologies. We describe details of the data workflows we use to provide both citizen scientists and researchers practical access to large volumes of ecoacoustic data. Finally, we propose a work in progress large-scale architecture for analysis driven by a hybrid cloud-and-local production-grade website.