A comparison of methods for classifying clinical samples based on proteomics data : a case study for statistical and machine learning approaches

The discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called “omics” disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems.

Impact of the introduction of machine gaming in Queensland on minor and major bingo

Material for this paper comes from as report commissioned by the Department of Family Services, Aboriginal and Islander Affairs. The report is the result of a multi strategy research project designed to assess the impact of gaming machines on the fundraising capacity of charitable and community organisations in Queensland. The study was conducted during the 1993 calendar year. The first Queensland gaming machine was commissioned on the 11 February, 1992 at 11.30 am in Brisbane at the Kedron Wavell Services Club. Eighteen more clubs followed that week. Six months later there were gaming machines in 335 clubs, and 250 hotels and taverns, representing a state wide total of 7,974 machines in operation. The 10,000 gaming machine was commissioned on the 18 March, 1993 and the 1,000 operational gaming machine site was opened on 18th February, 1994.

A simulated annealing algorithm for energy efficient virtual machine placement

Improving energy efficiency has become increasingly important in data centers in recent years to reduce the rapidly growing tremendous amounts of electricity consumption. The power dissipation of the physical servers is the root cause of power usage of other systems, such as cooling systems. Many efforts have been made to make data centers more energy efficient. One of them is to minimize the total power consumption of these servers in a data center through virtual machine consolidation, which is implemented by virtual machine placement. The placement problem is often modeled as a bin packing problem. Due to the NP-hard nature of the problem, heuristic solutions such as First Fit and Best Fit algorithms have been often used and have generally good results. However, their performance leaves room for further improvement. In this paper we propose a Simulated Annealing based algorithm, which aims at further improvement from any feasible placement. This is the first published attempt of using SA to solve the VM placement problem to optimize the power consumption. Experimental results show that this SA algorithm can generate better results, saving up to 25 percentage more energy than First Fit Decreasing in an acceptable time frame.

Energy-efficient virtual machine placement in data centers by genetic algorithm

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

Probability analysis of machine angle stability with non-gaussian wind power input

The security of power transfer across a given transmission link is typically a steady state assessment. This paper develops tools to assess machine angle stability as affected by a combination of faults and uncertainty of wind power using probability analysis. The paper elaborates on the development of the theoretical assessment tool and demonstrates its efficacy using single machine infinite bus system.

Cutting down the Cypress leylandii, pittosporums, and cotoneasters on your neighbours' land - the resolution of spite hedges

Queensland, New South Wales, and the United Kingdom have enacted legislation that governs what are colloquially known as spite hedges. These are barriers, commonly horticultural, that once constructed, block the view or sunlight from a neighbouring property. The matter was also recently raised in the Tasmanian Parliament. This article examines whether legislation should be enacted to deal with this issue, and if so, what is the regulatory model that need be adopted. The conclusion is that a layered nuanced response is needed to balance the interests and obligations of neighbouring landowners.

A case-control study of ambient heat exposure and urolithiasis among outdoor workers in a shipbuilding company, Guangzhou, China

Higher ambient temperatures will increase heat stress on workers, leading to impacts upon their individual health and productivity. In particular, research has indicated that higher ambient temperatures can increase the prevalence of urolithiasis. This thesis examines the relationship between ambient heat exposure and urolithiasis among outdoor workers in a shipbuilding company in Guangzhou, China, and makes recommendations for minimising the possible impacts of high ambient temperatures on urolithiasis. A retrospective 1:4 matched case-control study was performed to investigate the association between ambient heat exposure and urolithiasis. Ambient heat exposure was characterised by total exposure time, type of work, department and length of service. The data were obtained from the affiliated hospital of the shipbuilding company under study for the period 2003 to 2010. A conditional logistic regression model was used to estimate the association between heat exposure and urolithiasis. This study found that the odds ratio (OR) of urolithiasis for total exposure time was 1.5 (95% confidence interval (CI): 1.2–1.8). Eight types of work in the shipbuilding company were investigated, including welder, assembler, production security and quality inspector, planing machine operator, spray painter, gas-cutting worker and indoor employee. Five out of eight types of work had significantly higher risks for urolithiasis, and four of the five mainly consisted of outdoors work with ORs of 4.4 (95% CI: 1.7–11.4) for spray painter, 3.8 (95% CI: 1.9–7.2) for welder, 2.7 (95% CI: 1.4–5.0) for production security and quality inspector, and 2.2 (95% CI: 1.1–4.3) for assembler, compared to the reference group (indoor employee). Workers with abnormal blood pressure (hypertension) were more likely to have urolithiasis with an OR of 1.6 (95% CI: 1.0–2.5) compared to those without hypertension. This study contributes to the understanding of the association between ambient heat exposure and urolithiasis among outdoor workers in China. In the context of global climate change, this is particularly important because rising temperatures are expected to increase the prevalence of urolithiasis among outdoor workers, putting greater pressure on productivity, occupational health management and health care systems. The results of this study have clear implications for public health policy and planning, as they indicate that more attention is required to protect outdoor workers from heat-related urolithiasis.

Machine prognostics based on health state estimation using SVM

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation, and can also improve productivity and enhance system safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and an assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of machines based on health state probability estimation and involving historical knowledge embedded in the closed loop diagnostics and prognostics systems. The technique uses a Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation, which can affect the accuracy of prediction. To validate the feasibility of the proposed model, real life historical data from bearings of High Pressure Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life. The results obtained were very encouraging and showed that the proposed prognostic system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

How to design extended finite state machine test models in Java

This chapter is a tutorial that teaches you how to design extended finite state machine (EFSM) test models for a system that you want to test. EFSM models are more powerful and expressive than simple finite state machine (FSM) models, and are one of the most commonly used styles of models for model-based testing, especially for embedded systems. There are many languages and notations in use for writing EFSM models, but in this tutorial we write our EFSM models in the familiar Java programming language. To generate tests from these EFSM models we use ModelJUnit, which is an open-source tool that supports several stochastic test generation algorithms, and we also show how to write your own model-based testing tool. We show how EFSM models can be used for unit testing and system testing of embedded systems, and for offline testing as well as online testing.

Cutting on action : interference strategies in contemporary art practice

The domestication of creative software and hardware has been a significant factor in the recent proliferation of still and moving image creation. Booming numbers of amateur image-makers have the resources, skills and ambitions to create and distribute their work on a mass scale. At the same time, contemporary art seems increasingly dominated by ‘post-medium’ practices that adopt and adapt the representational techniques of mass culture, rather than overtly reject or oppose them. As a consequence of this network of forces, the field of image and video production is no longer the exclusive specialty of art and the mass media, and art may no longer be the most prominent watchdog of mass image culture. Intuitively and intentionally, contemporary artists are responding to these shifting conditions. From the position of a creative practitioner and researcher, this paper examines the strategies that contemporary artists use to engage with the changing relationships between image culture, lived experience and artistic practice. By examining the intersections between W.J.T. Mitchell’s detailed understanding of visual literacy and Jacques Derrida’s philosophical models of reading and writing, I identify ‘editing’ as a broad methodology that describes how practitioners creatively and critically engage with the field of still and moving images. My contention is that by emphasising the intersections of looking and making, ‘reading’ and ‘writing’, artists provide crucial jump cuts, pauses and distortions in the medley of our mediated experiences.

Optimal power system stabilizer tuning in multi-machine system via an improved differential evolution

Power system stabilizer (PSS) is one of the most important controllers in modern power systems for damping low frequency oscillations. Many efforts have been dedicated to design the tuning methodologies and allocation techniques to obtain optimal damping behaviors of the system. Traditionally, it is tuned mostly for local damping performance, however, in order to obtain a globally optimal performance, the tuning of PSS needs to be done considering more variables. Furthermore, with the enhancement of system interconnection and the increase of system complexity, new tools are required to achieve global tuning and coordination of PSS to achieve optimal solution in a global meaning. Differential evolution (DE) is a recognized as a simple and powerful global optimum technique, which can gain fast convergence speed as well as high computational efficiency. However, as many other evolutionary algorithms (EA), the premature of population restricts optimization capacity of DE. In this paper, a modified DE is proposed and applied for optimal PSS tuning of 39-Bus New-England system. New operators are introduced to reduce the probability of getting premature. To investigate the impact of system conditions on PSS tuning, multiple operating points will be studied. Simulation result is compared with standard DE and particle swarm optimization (PSO).

Correct procedures and cutting corners: a qualitative study of women's occupational health and safety in a beauty therapy industry

Objective: To examine the context of occupational health and safety related to blood-borne communicable diseases practice. Methods: A case study approach using qualitative semi-structured interviews with five key informants who represented different sectors of the beauty therapy industry in South Australia. Results: Four main themes were identified: (i) exposure to blood and blood-borne communicable diseases; (ii) prevention in practice; (iii) OH&S problems; and (iv) industry needs. Conclusion: Key OH&S issues in the beauty therapy industry include: power relationships between employers and employees, equipment costs, the need for more continuing education, and monitoring of practitioners. Implications: Economic constraints, continuing education, and government regulation of the beauty therapy industry are highlighted as significant areas for further consideration in addressing the OH&S needs of practitioners and their clients.

Energy efficient virtual machine placement in data centers

Electricity cost has become a major expense for running data centers and server consolidation using virtualization technology has been used as an important technology to improve the energy efficiency of data centers. In this research, a genetic algorithm and a simulation-annealing algorithm are proposed for the static virtual machine placement problem that considers the energy consumption in both the servers and the communication network, and a trading algorithm is proposed for dynamic virtual machine placement. Experimental results have shown that the proposed methods are more energy efficient than existing solutions.

The primary school as a logic machine

This paper makes a case for thinking about the primary school as a logic machine (apparatus) as a way of thinking about processes of in-school stratification. Firstly we discuss related literature on in-school stratification in primary schools, particularly as it relates to literacy learning. Secondly we explain how school reform can be thought about in terms of the idea of the machine or apparatus. In which case the processes of in-school stratification can be mapped as more than simply concerns about school organisation (such as students grouping) but also involve a politics of truth, played out in each school, that constitutes school culture and what counts as ‘good’ pedagogy. Thirdly, the chapter will focus specifically on research conducted into primary schools in the Northern Suburbs of Adelaide, one of the most educationally disadvantaged regions in Australia, as a case study of the relationship between in-school stratification and the reproduction of inequality. We will draw from more than 20 years of ethnographic work in primary school in the northern suburbs of Adelaide and provide a snapshot of a recent attempt to improve literacy achievement in a few Northern Suburbs public primary schools (SILA project). The SILA project, through diagnostic reviews, has provided a significant analysis of the challenges facing policy and practice in such challenging school contexts that also maps onto existing (inter)national research. These diagnostic reviews said ‘hard things’ that required attention by SILA schools and these included: · an over reliance on whole class, low level, routine tasks and hence a lack of challenge and rigour in the learning tasks offered to students ; · a focus on the 'code breaking' function of language at the expense of richer conceptualisations of literacy that might guide teachers’ understanding of challenging pedagogies ; · the need for substantial shifts in the culture of schools, especially unsettling deficit views of students and their communities ; · a need to provide a more ‘consistent’ approach to teaching literacy across the school; · a need to focus School Improvement Plans in order to implement a clear focus on literacy learning; and, · a need to sustain professional learning to produce new knowledge and practice . The paper will conclude with suggestions for further research and possible reform projects into the primary school as a logic machine.

A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation technology. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches consider the energy consumption by physical machines only, but do not consider the energy consumption in communication network, in a data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement. In our preliminary research, we have proposed a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both physical machines and the communication network in a data center. Aiming at improving the performance and efficiency of the genetic algorithm, this paper presents a hybrid genetic algorithm for the energy-efficient virtual machine placement problem. Experimental results show that the hybrid genetic algorithm significantly outperforms the original genetic algorithm, and that the hybrid genetic algorithm is scalable.