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.

Front page schools, back page schools : a case study of factors perceived to affect academic performance in five Papua New Guinea secondary schools

Papua New Guinea has reformed its colonial established education system and made huge investments with the help of donors to achieve equal access and quality education for all its citizens. Despite this national aspiration and these policy reforms and investments, secondary schools that enrol grade 9 students who are relatively equal in education ability show huge disparities in their grade 10 academic performances. This study examined perceptions of students, teachers and principals regarding factors affecting the disparity in academic performance in the context of a developing country. The central question for the study is: What are the perceptions of students and teachers of the factors that affect disparities in secondary schools' academic performance? This qualitative case study involved two high and three low academic performing secondary schools in Western Highlands Province of Papua New Guinea. Primary data were collected through focus groups and semi-structured interviews involving 112 participants. Students and teachers are key participants in this study, as it intends to find out the realities of schools, yet they are an under-researched group. A postcolonial and sense of community conceptual framework was developed for the analysis of the participants. perceptions. In addition, scholarship on school effectiveness and equity in education informed the interpretation of the findings. Three themes were evident in participants. views. First, participants expressed their view that differences in academic performance were related to the adequacy and equitability of resources. The inequities in resource inputs led some of them to coin the metaphor of .back page and front page. schools. Second, many expressed the view that deficiencies in implementing bilingual education, given the difficulty of catering for 800 vernacular languages, contribute to poor English proficiency and subsequent poor academic performance. Finally, participants believed that, in order to have a positive school culture, it is necessary for educators to recognise and respect contemporary students. identities, communal/tribal membership and needs. This study has implications for national education policy on resource allocation to address equality and equity, bilingual education and teacher education. Moreover, as the study found that high academic performance in this context is also influenced by intra-school social relationships, these relationships need to be nurtured. When appropriately nurtured, they become an important factor in sustaining quality education for all secondary school students. This thesis has laid the foundations for further research and invites further investigations into policy and implementation of school reforms aimed at improving academic achievement.

Four years on – are the Gazelles still running? A longitudinal study of firm performance after a period of rapid growth

Gazelles, or very rapidly growing firms, are important because they contribute disproportionately to economic growth. There is a concern that some of these firms pursue growth too aggressively resulting in lower subsequent performance. We investigate the relationship between growth and subsequent profitability for gazelle firms, and how this is moderated by firm strategy. Previous empirical research regarding the growth-profitability relationship for firms in general is rather inconclusive, with only one study specifically investigating gazelle firms. Likewise, there are theoretical arguments both for and against growth leading to profitability that equally apply to gazelle firms. Further, while contingency theory might suggest the relationship depends on the firm’s strategy, earlier studies have not investigated this relationship. We address these questions using longitudinal data (seven years) for a sample of 964 Danish Gazelle firms. Our study finds a clear positive relationship between growth and subsequent profitability among gazelle firms. Moreover, this relationship is stronger for firms pursuing a broad market strategy rather than a focus or niche strategy. An important managerial implication is that the growth strategy should be clearly integrated with the general strategic orientation of the firm.

Thermal performance of non-load bearing LSF walls using numerical studies

Fire safety of light gauge cold-formed steel frame (LSF) wall systems is significant to the build-ing design. Gypsum plasterboard is widely used as a fire safety material in the building industry. It contains gypsum (CaSO4.2H2O), Calcium Carbonate (CaCO3) and most importantly free and chemically bound water in its crystal structure. The dehydration of the gypsum and the decomposition of Calcium Carbonate absorb heat, which gives the gypsum plasterboard fire resistant qualities. Recently a new composite panel system was developed, where a thin insulation layer was used externally between two plasterboards to improve the fire performance of LSF walls. In this research, finite element thermal models of both the traditional LSF wall panels with cavity insulation and the new LSF composite wall panels were developed to simulate their thermal behaviour under standard and realistic design fire conditions. Suitable thermal properties of gypsum plaster-board, insulation materials and steel were used. The developed models were then validated by comparing their results with fire test results. This paper presents the details of the developed finite element models of non-load bearing LSF wall panels and the thermal analysis results. It has shown that finite element models can be used to simulate the thermal behaviour of LSF walls with varying configurations of insulations and plasterboards. The results show that the use of cavity insulation was detrimental to the fire rating of LSF walls while the use of external insulation offered superior thermal protection. Effects of real fire conditions are also presented.

The relationship between academic library usage and perceived personal performance in Kuwait

Academic libraries around the world often have to justify high maintenance costs. High maintenance costs of university libraries are often justified by the belief that regular use of an academic library improves the grades of students. However, this is a difficult statement to support, therefore demonstrating the link between library use and student outcomes is critical to ensuring that library investment continues. Questionnaires and interviews were conducted and the findings were analysed to derive users’ perceptions. The findings revealed interesting results regarding how users make use of the library and how users feel the library improves their personal performance. Overall, the perception of all three groups of the academic libraries within Kuwait is positive, however many users are dissatisfied with some academic library services. Students answered positively regarding their grades and use of the academic library. Academics and administrators were generally positive and offered an experienced insight into the quality of the library. This study offers the first perception based results in Kuwait. The inclusion of administrators’ perceptions is also novel in terms of the Gulf States. A refined model was designed based on the overall findings within the study. This model can be applied to any academic library, regardless of size or collection type. Based on findings, the researcher recommends taking the following points into consideration in order to improve library services and facilities for all users. Improvements could be made in the structure of library training courses and academic libraries should be providing flexible spaces for individuals and group study as well as social activities.

Towards spontaneous facial expression recognition in real-world video

Facial expression is an important channel of human social communication. Facial expression recognition (FER) aims to perceive and understand emotional states of humans based on information in the face. Building robust and high performance FER systems that can work in real-world video is still a challenging task, due to the various unpredictable facial variations and complicated exterior environmental conditions, as well as the difficulty of choosing a suitable type of feature descriptor for extracting discriminative facial information. Facial variations caused by factors such as pose, age, gender, race and occlusion, can exert profound influence on the robustness, while a suitable feature descriptor largely determines the performance. Most present attention on FER has been paid to addressing variations in pose and illumination. No approach has been reported on handling face localization errors and relatively few on overcoming facial occlusions, although the significant impact of these two variations on the performance has been proved and highlighted in many previous studies. Many texture and geometric features have been previously proposed for FER. However, few comparison studies have been conducted to explore the performance differences between different features and examine the performance improvement arisen from fusion of texture and geometry, especially on data with spontaneous emotions. The majority of existing approaches are evaluated on databases with posed or induced facial expressions collected in laboratory environments, whereas little attention has been paid on recognizing naturalistic facial expressions on real-world data. This thesis investigates techniques for building robust and high performance FER systems based on a number of established feature sets. It comprises of contributions towards three main objectives: (1) Robustness to face localization errors and facial occlusions. An approach is proposed to handle face localization errors and facial occlusions using Gabor based templates. Template extraction algorithms are designed to collect a pool of local template features and template matching is then performed to covert these templates into distances, which are robust to localization errors and occlusions. (2) Improvement of performance through feature comparison, selection and fusion. A comparative framework is presented to compare the performance between different features and different feature selection algorithms, and examine the performance improvement arising from fusion of texture and geometry. The framework is evaluated for both discrete and dimensional expression recognition on spontaneous data. (3) Evaluation of performance in the context of real-world applications. A system is selected and applied into discriminating posed versus spontaneous expressions and recognizing naturalistic facial expressions. A database is collected from real-world recordings and is used to explore feature differences between standard database images and real-world images, as well as between real-world images and real-world video frames. The performance evaluations are based on the JAFFE, CK, Feedtum, NVIE, Semaine and self-collected QUT databases. The results demonstrate high robustness of the proposed approach to the simulated localization errors and occlusions. Texture and geometry have different contributions to the performance of discrete and dimensional expression recognition, as well as posed versus spontaneous emotion discrimination. These investigations provide useful insights into enhancing robustness and achieving high performance of FER systems, and putting them into real-world applications.

Scheduling techniques to optimise rail operations

In Australia, railway systems play a vital role in transporting the sugarcane crop from farms to mills. The sugarcane transport system is very complex and uses daily schedules, consisting of a set of locomotives runs, to satisfy the requirements of the mill and harvesters. The total cost of sugarcane transport operations is very high; over 35% of the total cost of sugarcane production in Australia is incurred in cane transport. Efficient schedules for sugarcane transport can reduce the cost and limit the negative effects that this system can have on the raw sugar production system. There are several benefits to formulating the train scheduling problem as a blocking parallel-machine job shop scheduling (BPMJSS) problem, namely to prevent two trains passing in one section at the same time; to keep the train activities (operations) in sequence during each run (trip) by applying precedence constraints; to pass the trains on one section in the correct order (priorities of passing trains) by applying disjunctive constraints; and, to ease passing trains by solving rail conflicts by applying blocking constraints and Parallel Machine Scheduling. Therefore, the sugarcane rail operations are formulated as BPMJSS problem. A mixed integer programming and constraint programming approaches are used to describe the BPMJSS problem. The model is solved by the integration of constraint programming, mixed integer programming and search techniques. The optimality performance is tested by Optimization Programming Language (OPL) and CPLEX software on small and large size instances based on specific criteria. A real life problem is used to verify and validate the approach. Constructive heuristics and new metaheuristics including simulated annealing and tabu search are proposed to solve this complex and NP-hard scheduling problem and produce a more efficient scheduling system. Innovative hybrid and hyper metaheuristic techniques are developed and coded using C# language to improve the solutions quality and CPU time. Hybrid techniques depend on integrating heuristic and metaheuristic techniques consecutively, while hyper techniques are the complete integration between different metaheuristic techniques, heuristic techniques, or both.

Structural performance of reinforced concrete beams repairing from spalling

The effectiveness of a repair work for the restoration of spalled reinforced concrete (r.c.) structures depends to a great extent, on their ability to restore the structural integrity of the r.c. element, to restore its serviceability and to protect the reinforcements from further deterioration. This paper presents results of a study concocted to investigate the structural performance of eight spalled r.c. beams repaired using two advanced repair materials in various zones for comparison purposes, namely a free flowing self compacting mortar (FFSCM) and a polymer Modified cementitious mortar (PMCM). The repair technique adopted was that for the repair of spalled concrete in which the bond between the concrete and steel was completely lost due to reinforcement corrosion or the effect of fire or impact. The beams used for the experiment were first cast, then hacked at various zones before they were repaired except for the control beam. The beam specimens were then loaded to failure under four point loadings. The structural response of each beam was evaluated in terms of first crack load, cracking behavior, crack pattern, deflection, variation of strains in the concrete and steel, collapse load and the modes of failure. The results of the test showed that, the repair materials applied on the various zones of the beams were able to restore more than 100% of the beams’ capacity and that FFSCM gave a better overall performance.