Meeting the challenge of establishing commercial mohair enterprises by building an interactive enterprise management and financial model

To assist in attracting investors into mohair production in Australia, a production and financial model was built as a learning and support tool. The work aimed to reduce search time and thinking costs about the impact of management strategies on financial feasibility. Various management strategies and assumptions applied to a case study with 300 breeding Angora does and eight variations. The results showed an internal rate of return for mohair ranging from 9.3% to 21.2% over 12 years, a median gross margin per effective hectare ranging from $82 to $167, cash at bank in year 12 ranging from $8,700 to $56,800 and net enterprise assets ranging from $69,900 to $155,700. A key benefit of the model was its ability to allow new farmers to explore potential management strategies and their assumptions about a future enterprise before investing.

From design for ecologically sustainability to facilities management through building intelligence and knowledge management

Ecological sustainability basically concerns environmental protection and social benefits. An ecologically sustainable development is based upon reduced energy usage, increased efficiency, and upheld social responsibility; and it should be properly evaluated by financial, environmental and social aspects. Council House 2 (CH2) is claimed to change the way of Australia approaches in ecologically sustainable design and construction. This is the ‘Six-Star design and built’ green star facility assessed by the Green Building Council of Australia (GBCA), and the 10-story city council building was completed and opened in 2006, totally A$11.3 million was invested for the sustainability features. CH2 protects the environment, when it compares with the old council house, and is expected to reduce electricity consumption by 85%; reduce gas consumption by 87%; produce only 13% of the emissions; and reduce water mains supply by 72%. In this paper, the author examines its design reports and the researches paper, in the form of knowledge base, to case-study how the sustainability, effectiveness and efficiency of CH2 work. By leveraging the existing CH2 sustainability knowledge, design and building professions can learn and imitate it in further ‘green’ design without ‘re-inventing the wheel’; facilities executives can also use the existing knowledge to identify steps to boost up the facilities’ operating efficiency.

The Technique of modern floristry, a comprehensive and practical course of training covering floral craftsmanship, merchandising of flowers, correct management and successful operation of flower stores. Lessons 1-29.

Mode of access: Internet.

Port administration and operation : a review of systems of management in vogue in various countries /

Includes index.

The steam engine indicator and its appliances. Being a comprehensive treatise for the use of constructing, erecting and operating engineers, superintendents, master mechanics, and students ... with many illustrations, rules, tables, and examples for obtaining the best results in the economical operation of all classes of steam, gas and ammonia engines ... Its correct use, management and care, derived from the author's practical and professional experience ...

Mode of access: Internet.

Remarks on the constitution of the Medical Department of the British Army : with a detail of hospital management, and an appendix, attempting to explain the action of causes in producing fever and the operation of remedies in effecting cure.

Mode of access: Internet.

Progress in employee-management cooperation in the federal service; report to the President, and background information on the first year of operation under the new Employee-management co-operation program.

Cover title.

Financial planning and project cost control techniques applied to building management

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Adapting prospective structural analysis to strengthen sustainable management and capacity building in community-based natural resource management contexts

Local communities collectively managing common pool resources can play an important role in sustainable management, but they often lack the skills and context-specific tools required for such management. The complex dynamics of social-ecological systems (SES), the need for management capacities, and communities’ limited empowerment and participation skills present challenges for community-based natural resource management (CBNRM) strategies. We analyzed the applicability of prospective structural analysis (PSA), a strategic foresight tool, to support decision making and to foster sustainable management and capacity building in CBNRM contexts and the modifications necessary to use the tool in such contexts. By testing PSA in three SES in Colombia, Mexico, and Argentina, we gathered information regarding the potential of this tool and its adaptation requirements. The results suggest that the tool can be adapted to these contexts and contribute to fostering sustainable management and capacity building. It helped identify the systems’ dynamics, thus increasing the communities’ knowledge about their SES and informing the decision-making process. Additionally, it drove a learning process that both fostered empowerment and built participation skills. The process demanded both time and effort, and required external monitoring and facilitation, but community members could be trained to master it. Thus, we suggest that the PSA technique has the potential to strengthen CBNRM and that other initiatives could use it, but they must be aware of these requirements.

BUILDING EFFICIENT AND COST-EFFECTIVE CLOUD-BASED BIG DATA MANAGEMENT SYSTEMS

In today’s big data world, data is being produced in massive volumes, at great velocity and from a variety of different sources such as mobile devices, sensors, a plethora of small devices hooked to the internet (Internet of Things), social networks, communication networks and many others. Interactive querying and large-scale analytics are being increasingly used to derive value out of this big data. A large portion of this data is being stored and processed in the Cloud due the several advantages provided by the Cloud such as scalability, elasticity, availability, low cost of ownership and the overall economies of scale. There is thus, a growing need for large-scale cloud-based data management systems that can support real-time ingest, storage and processing of large volumes of heterogeneous data. However, in the pay-as-you-go Cloud environment, the cost of analytics can grow linearly with the time and resources required. Reducing the cost of data analytics in the Cloud thus remains a primary challenge. In my dissertation research, I have focused on building efficient and cost-effective cloud-based data management systems for different application domains that are predominant in cloud computing environments. In the first part of my dissertation, I address the problem of reducing the cost of transactional workloads on relational databases to support database-as-a-service in the Cloud. The primary challenges in supporting such workloads include choosing how to partition the data across a large number of machines, minimizing the number of distributed transactions, providing high data availability, and tolerating failures gracefully. I have designed, built and evaluated SWORD, an end-to-end scalable online transaction processing system, that utilizes workload-aware data placement and replication to minimize the number of distributed transactions that incorporates a suite of novel techniques to significantly reduce the overheads incurred both during the initial placement of data, and during query execution at runtime. In the second part of my dissertation, I focus on sampling-based progressive analytics as a means to reduce the cost of data analytics in the relational domain. Sampling has been traditionally used by data scientists to get progressive answers to complex analytical tasks over large volumes of data. Typically, this involves manually extracting samples of increasing data size (progressive samples) for exploratory querying. This provides the data scientists with user control, repeatable semantics, and result provenance. However, such solutions result in tedious workflows that preclude the reuse of work across samples. On the other hand, existing approximate query processing systems report early results, but do not offer the above benefits for complex ad-hoc queries. I propose a new progressive data-parallel computation framework, NOW!, that provides support for progressive analytics over big data. In particular, NOW! enables progressive relational (SQL) query support in the Cloud using unique progress semantics that allow efficient and deterministic query processing over samples providing meaningful early results and provenance to data scientists. NOW! enables the provision of early results using significantly fewer resources thereby enabling a substantial reduction in the cost incurred during such analytics. Finally, I propose NSCALE, a system for efficient and cost-effective complex analytics on large-scale graph-structured data in the Cloud. The system is based on the key observation that a wide range of complex analysis tasks over graph data require processing and reasoning about a large number of multi-hop neighborhoods or subgraphs in the graph; examples include ego network analysis, motif counting in biological networks, finding social circles in social networks, personalized recommendations, link prediction, etc. These tasks are not well served by existing vertex-centric graph processing frameworks whose computation and execution models limit the user program to directly access the state of a single vertex, resulting in high execution overheads. Further, the lack of support for extracting the relevant portions of the graph that are of interest to an analysis task and loading it onto distributed memory leads to poor scalability. NSCALE allows users to write programs at the level of neighborhoods or subgraphs rather than at the level of vertices, and to declaratively specify the subgraphs of interest. It enables the efficient distributed execution of these neighborhood-centric complex analysis tasks over largescale graphs, while minimizing resource consumption and communication cost, thereby substantially reducing the overall cost of graph data analytics in the Cloud. The results of our extensive experimental evaluation of these prototypes with several real-world data sets and applications validate the effectiveness of our techniques which provide orders-of-magnitude reductions in the overheads of distributed data querying and analysis in the Cloud.

The role of knowledge management and renewal in building innovation performance

Tämän työn tavoitteena oli selvittää tietojohtamisen eri käytäntöjen vaikutusta oppimiseen, uudistumiseen sekä yrityksen innovaatiokyvykkyyteen. Työssä on keskitytty erityisesti sellaisiin tietojohtamisen käytäntöihin, jotka edistävät oppimista ja uusiutumista yrityksissä. Työssä on käytetty tilastollisia menetelmiä, muun muassa faktorianalyysia, korrelaatioanalyysia sekä regressiota, analysoitaessa 259 suomalaisesta yrityksestä kerättyä kyselydataa niiden tietojohtamisen käytöntöihin ja aineettomaan pääomaan liittyen. Analyysi osoittaa, että useat tietojohtamisen käytännöt vaikuttavat positiivisesti yrityksen uudistumiseen ja sitä kautta innovaatiokyvykkyyteen. Henkilöstön kouluttaminen sekä parhaiden käytäntöjen kerääminen ja soveltaminen yrityksessä ovat positiivisesti yhteydessä innovaatiokyvykkyyteen. Henkilöstön kouluttamisella on merkittävin suora vaikutus innovaatiokyvykkyyteen ja tässä työssä on esitetty, että koulutuksen tarjoamisen suurin vaikutus on oppimismyönteisen kulttuurin kehittyminen yrityksiin sen sijaan, että koulutuksella pyrittäisiin vain parantamaan tehtäväkenttään liittyviä taitoja ja tietoja. Henkilöstön kouluttaminen, parhaat käytännöt sekä sosialisaatiossa tapahtuva tiedon vaihto ja suhteiden solmiminen vaikuttavat positiivisesti uudistumispääomaan. Työn tulosten perusteella uudistumispääomalla on merkittävä rooli innovaatioiden syntymisessä yrityksissä. Uudistumispääoma medioi koulutuksen, parhaiden käytäntöjen ja mahdollisesti myös sosialisaation vaikutusta innovaatiokyvykkyyteen ja on näin merkittävä osa innovaatioiden syntyä yrityksissä. Innovaatiokyvykkyyden osatekijöiden ymmärtäminen voi auttaa johtajia ja esimiehiä keskittämään huomionsa tiettyihin tietojohtamisen käytäntöihin edistääkseen innovaatioiden syntymistä yrityksessä sen sijaan, että he pyrkisivät vain vaikuttamaan innovaatioprosessiin.

Power management and control strategies for efficient operation of a solar power dominated hybrid DC microgrid for remote power applications

In this paper, a hybrid DC microgrid consisting of a diesel generator with a rectifier, a solar photovoltaic (PV) system, and a battery energy storage system is presented in relation to an effective power management strategy and different control techniques are adopted to power electronic interfaces. The solar PV and battery energy storage systems are considered as the main sources of energy sources that supply the load demand on a daily basis whereas the diesel generator is used as a backup for the emergency operation of the microgrid. All system components are connected to a common DC bus through an appropriate power electronics devices (e.g., rectifier systems, DC/DC converter). Also a detailed sizing philosophy of all components along with the energy management strategy is proposed. Energy distribution pattern of each individual component has been conducted based on the monthly basis along with a power management algorithm. The power delivered by the solar PV system and diesel generator is controlled via DC-DC converterand excitation controllers which are designed based on a linearquadratic regulator (LQR) technique as as proportional integral (PI)controllers. The component level power distribution is investigatedusing these controllers under fluctuating load and solar irradiationconditions and comparative results are presented.

Report on relationship management and culture change

Brisbane Water (BW), a commercialised business arm of Brisbane City Council (BCC) entered into an alliance with a number of organisations from the private sector in order to design, construct, commission and undertake upgrades to three existing wastewater treatment plants located at Sandgate, Oxley Creek, and Wacol in Brisbane. The alliance project is called the Brisbane Water Environmental Alliance (BWEA). This report details the efforts of a team of researchers from the School of Management at Queensland University of Technology to investigate this alliance. This is the second report on this project, and is called Stage 2 of the research. At the time that Stage 2 of the research project was conducted, the BWEA project was nearing completion with a further 8 months remaining before project completion. The aim of this report is to explore individuals’ perceptions of the effectiveness and functioning of the BWEA project in the latter stages of the project. The second aim of this report is to analyse the longitudinal findings of this research project by integrating the findings from Stage 1 and Stage 2 of the project. This long-term analysis of the functioning and effectiveness of the alliance is important because at the current time, researchers have little knowledge of the group developmental processes that occur in large-scale alliances over time. Stage 2 of this research project has a number of aims including assessing performance of the BWEA project from the point of view of a range of stakeholders including the alliance board and alliance management team, alliance staff, and key stakeholders from the client organisation (Brisbane Water). Data were collected using semi-structured interviews with 18 individuals including two board members, one external facilitator, and four staff members from the client organisation. Analysis involved coding the interview transcripts in terms of the major issues that were reported by interviewees.