Managing university records and documents in the world of governance, audit and risk: Case studies from South Africa and Malawi

There are enormous benefits for any organisation from practising sound records management. In the context of a public university, the importance of good records management includes: facilitating the achievement the university’s mandate; enhancing efficiency of the university; maintaining a reliable institutional memory; promoting trust; responding to an audit culture; enhancing university competitiveness; supporting the university’s fiduciary duty; demonstrating transparency and accountability; and fighting corruption. Records scholars and commentators posit that effective recordkeeping is an essential underpinning of good governance. Although there is a portrayal of positive correlation, recordkeeping struggles to get the same attention as that given to the governance. Evidence abounds of cases of neglect of recordkeeping in universities and other institutions in Sub-Saharan Africa. The apparent absence of sound recordkeeping provided a rationale for revisiting some universities in South Africa and Malawi in order to critically explore the place of recordkeeping in an organisation’s strategy in order to develop an alternative framework for managing records and documents in an era where good governance is a global agenda. The research is a collective case study in which multiple cases are used to critically explore the relationship between recordkeeping and governance. As qualitative research that belongs in the interpretive tradition of enquiry, it is not meant to suggest prescriptive solutions to general recordkeeping problems but rather to provide an understanding of the challenges and opportunities that arise in managing records and documents in the world of governance, audit and risk. That is: what goes on in the workplace; what are the problems; and what alternative approaches might address any existing problem situations. Research findings show that some institutions are making good use of their governance structures and other drivers for recordkeeping to put in place sound recordkeeping systems. Key governance structures and other drivers for recordkeeping identified include: laws and regulations; governing bodies; audit; risk; technology; reforms; and workplace culture. Other institutions are not managing their records and documents well despite efforts to improve their governance systems. They lack recordkeeping capacity. Areas that determine recordkeeping capacity include: availability of records management policy; capacity for digital records; availability of a records management unit; senior management support; level of education and training of records management staff; and systems and procedures for storage, retrieval and dispositions of records. Although this research reveals that the overall recordkeeping in the selected countries has slightly improved compared with the situation other researchers found a decade ago, it remains unsatisfactory and disjointed from governance. The study therefore proposes governance recordkeeping as an approach to managing records and documents in the world of governance, audit and risk. The governance recordkeeping viewpoint considers recordkeeping as a governance function that should be treated in the same manner as other governance functions such as audit and risk management. Additionally, recordkeeping and governance should be considered as symbiotic elements of a strategy. A strategy that neglects recordkeeping may not fulfil the organisation’s objectives effectively.

Optimised wheat root architecture for increased yield and yield stability in the face of a changing climate.

This project provided information, selection techniques and strategies to facilitate the development of high-yielding, stay-green wheat varieties for Australian growers through: a) Improved understanding of the relationships between seminal root traits and other root- and shoot-related traits in determining high-yielding, stay-green phenotypes. b). Molecular markers and rapid phenotypic screening methods that allow selection in breeding programs and identification of genetic regions controlling favourable traits. c). Identification of traits leading to high-yielding, stay-green phenotypes for particular target populations of environments using computer simulation studies.

Carbon losses in terrestrial hydrological pathways in sugarcane cropping systems of Australia

Climate change and carbon (C) sequestration are a major focus of research in the twenty-first century. Globally, soils store about 300 times the amount of C that is released per annum through the burning of fossil fuels (Schulze and Freibauer 2005). Land clearing and introduction of agricultural systems have led to rapid declines in soil C reserves. The recent introduction of conservation agricultural practices has not led to a reversing of the decline in soil C content, although it has minimized the rate of decline (Baker et al. 2007; Hulugalle and Scott 2008). Lal (2003) estimated the quantum of C pools in the atmosphere, terrestrial ecosystems, and oceans and reported a “missing C” component in the world C budget. Though not proven yet, this could be linked to C losses through runoff and soil erosion (Lal 2005) and a lack of C accounting in inland water bodies (Cole et al. 2007). Land management practices to minimize the microbial respiration and soil organic C (SOC) decline such as minimum tillage or no tillage were extensively studied in the past, and the soil erosion and runoff studies monitoring those management systems focused on other nutrients such as nitrogen (N) and phosphorus (P).

Heterosis in locally adapted sorghum genotypes and potential of hybrids for increased productivity in contrasting environments in Ethiopia

Increased productivity in sorghum has been achieved in the developed world using hybrids. Despite their yield advantage, introduced hybrids have not been adopted in Ethiopia due to the lack of adaptive traits, their short plant stature and small grain size. This study was conducted to investigate hybrid performance and the magnitude of heterosis of locally adapted genotypes in addition to introduced hybrids in three contrasting environments in Ethiopia. In total, 139 hybrids, derived from introduced seed parents crossed with locally adapted genotypes and introduced R lines, were evaluated. Overall, the hybrids matured earlier than the adapted parents, but had higher grain yield, plant height, grain number and grain weight in all environments. The lowland adapted hybrids displayed a mean better parent heterosis (BPH) of 19%, equating to 1160 kg ha− 1 and a 29% mean increase in grain yield, in addition to increased plant height and grain weight, in comparison to the hybrids derived from the introduced R lines. The mean BPH for grain yield for the highland adapted hybrids was 16% in the highland and 52% in the intermediate environment equating to 698 kg ha− 1 and 2031 kg ha− 1, respectively, in addition to increased grain weight. The magnitude of heterosis observed for each hybrid group was related to the genetic distance between the parental lines. The majority of hybrids also showed superiority over the standard check varieties. In general, hybrids from locally adapted genotypes were superior in grain yield, plant height and grain weight compared to the high parents and introduced hybrids indicating the potential for hybrids to increase productivity while addressing farmers' required traits.

Rule Generalisation in Intrusion Detection Systems using Snort

Intrusion Detection Systems (IDSs) provide an important layer of security for computer systems and networks, and are becoming more and more necessary as reliance on Internet services increases and systems with sensitive data are more commonly open to Internet access. An IDS’s responsibility is to detect suspicious or unacceptable system and network activity and to alert a systems administrator to this activity. The majority of IDSs use a set of signatures that define what suspicious traffic is, and Snort is one popular and actively developing open-source IDS that uses such a set of signatures known as Snort rules. Our aim is to identify a way in which Snort could be developed further by generalising rules to identify novel attacks. In particular, we attempted to relax and vary the conditions and parameters of current Snort rules, using a similar approach to classic rule learning operators such as generalisation and specialisation. We demonstrate the effectiveness of our approach through experiments with standard datasets and show that we are able to detect previously undetected variants of various attacks. We conclude by discussing the general effectiveness and appropriateness of generalisation in Snort based IDS rule processing. Keywords: anomaly detection, intrusion detection, Snort, Snort rules

Sorghum Crop Modeling and Its Utility in Agronomy and Breeding

Crop models are simplified mathematical representations of the interacting biological and environmental components of the dynamic soil–plant–environment system. Sorghum crop modeling has evolved in parallel with crop modeling capability in general, since its origins in the 1960s and 1970s. Here we briefly review the trajectory in sorghum crop modeling leading to the development of advanced models. We then (i) overview the structure and function of the sorghum model in the Agricultural Production System sIMulator (APSIM) to exemplify advanced modeling concepts that suit both agronomic and breeding applications, (ii) review an example of use of sorghum modeling in supporting agronomic management decisions, (iii) review an example of the use of sorghum modeling in plant breeding, and (iv) consider implications for future roles of sorghum crop modeling. Modeling and simulation provide an avenue to explore consequences of crop management decision options in situations confronted with risks associated with seasonal climate uncertainties. Here we consider the possibility of manipulating planting configuration and density in sorghum as a means to manipulate the productivity–risk trade-off. A simulation analysis of decision options is presented and avenues for its use with decision-makers discussed. Modeling and simulation also provide opportunities to improve breeding efficiency by either dissecting complex traits to more amenable targets for genetics and breeding, or by trait evaluation via phenotypic prediction in target production regions to help prioritize effort and assess breeding strategies. Here we consider studies on the stay-green trait in sorghum, which confers yield advantage in water-limited situations, to exemplify both aspects. The possible future roles of sorghum modeling in agronomy and breeding are discussed as are opportunities related to their synergistic interaction. The potential to add significant value to the revolution in plant breeding associated with genomic technologies is identified as the new modeling frontier.

Epigenetics and alternative splicing

Dissertação de Mestrado, Oncobiologia: Mecanismos Moleculares do Cancro, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2015

Natural Disasters and Comparative State-Formation and Nation-Building: Earthquakes in Argentina and Chile (1822-1939)

Natural disasters in Argentina and Chile played a significant role in the state-formation and nation-building process (1822-1939). This dissertation explores state and society responses to earthquakes by studying public and private relief efforts reconstruction plans, crime and disorder, religious interpretations of catastrophes, national and transnational cultures of disaster, science and technology, and popular politics. Although Argentina and Chile share a political border and geological boundary, the two countries provide contrasting examples of state formation. Most disaster relief and reconstruction efforts emanated from the centralized Chilean state in Santiago. In Argentina, provincial officials made the majority of decisions in a catastrophe’s aftermath. Patriotic citizens raised money and collected clothing for survivors that helped to weave divergent regions together into a nation. The shared experience of earthquakes in all regions of Chile created a national disaster culture. Similarly, common disaster experiences, reciprocal relief efforts, and aid commissions linked Chileans with Western Argentine societies and generated a transnational disaster culture. Political leaders viewed reconstruction as opportunities to implement their visions for the nation on the urban landscape. These rebuilding projects threatened existing social hierarchies and often failed to come to fruition. Rebuilding brought new technologies from Europe to the Southern Cone. New building materials and systems, however, had to be adapted to the South American economic and natural environment. In a catastrophe’s aftermath, newspapers projected images of disorder and the authorities feared lawlessness and social unrest. Judicial and criminal records, however, show that crime often decreased after a disaster. Finally, nineteenth-century earthquakes heightened antagonism and conflict between the Catholic Church and the state. Conservative clergy asserted that disasters were divine punishments for the state’s anti-clerical measures and later railed against scientific explanations of earthquakes.

Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.

Development and validation of a computationally efficient pseudo 3D model for planar SOFC integrated with a heating furnace

Efficient numerical models facilitate the study and design of solid oxide fuel cells (SOFCs), stacks, and systems. Whilst the accuracy and reliability of the computed results are usually sought by researchers, the corresponding modelling complexities could result in practical difficulties regarding the implementation flexibility and computational costs. The main objective of this article is to adapt a simple but viable numerical tool for evaluation of our experimental rig. Accordingly, a model for a multi-layer SOFC surrounded by a constant temperature furnace is presented, trained and validated against experimental data. The model consists of a four-layer structure including stand, two interconnects, and PEN (Positive electrode-Electrolyte-Negative electrode); each being approximated by a lumped parameter model. The heating process through the surrounding chamber is also considered. We used a set of V-I characteristics data for parameter adjustment followed by model verification against two independent sets of data. The model results show a good agreement with practical data, offering a significant improvement compared to reduced models in which the impact of external heat loss is neglected. Furthermore, thermal analysis for adiabatic and non-adiabatic process is carried out to capture the thermal behaviour of a single cell followed by a polarisation loss assessment. Finally, model-based design of experiment is demonstrated for a case study.

User interaction monitoring and analysis framework

An overview is given of a user interaction monitoring and analysis framework called BaranC. Monitoring and analysing human-digital interaction is an essential part of developing a user model as the basis for investigating user experience. The primary human-digital interaction, such as on a laptop or smartphone, is best understood and modelled in the wider context of the user and their environment. The BaranC framework provides monitoring and analysis capabilities that not only records all user interaction with a digital device (e.g. smartphone), but also collects all available context data (such as from sensors in the digital device itself, a fitness band or a smart appliances). The data collected by BaranC is recorded as a User Digital Imprint (UDI) which is, in effect, the user model and provides the basis for data analysis. BaranC provides functionality that is useful for user experience studies, user interface design evaluation, and providing user assistance services. An important concern for personal data is privacy, and the framework gives the user full control over the monitoring, storing and sharing of their data.

A pro-active and dynamic prediction assistance using BaranC framework

Monitoring user interaction activities provides the basis for creating a user model that can be used to predict user behaviour and enable user assistant services. The BaranC framework provides components that perform UI monitoring (and collect all associated context data), builds a user model, and supports services that make use of the user model. In this case study, a Next-App prediction service is built to demonstrate the use of the framework and to evaluate the usefulness of such a prediction service. Next-App analyses a user's data, learns patterns, makes a model for a user, and finally predicts based on the user model and current context, what application(s) the user is likely to want to use. The prediction is pro-active and dynamic; it is dynamic both in responding to the current context, and also in that it responds to changes in the user model, as might occur over time as a user's habits change. Initial evaluation of Next-App indicates a high-level of satisfaction with the service.

Stability and smoothness improvements for an underactuated biped with a tail

In this work we present an important improvement in our model of biped mechanism that allows the elevation in a stable form of the system's feet during the execution of trajectories. This improvement allows for simpler trajectory planning and also facilitates the reduction of losses in the collision between the feet and the ground. On the other hand, we add to the design phase the study of the displacement of the Zero Moment Point, as well as the variation of the normal component of the ground reaction force during the motion of the system. Consideration of the above mentioned magnitudes in the design phase allows us to design the necessary support area of the system. These magnitudes will be used as a smoothness criterion of the ground contact to facilitate the selection of robot parameters and trajectories.

Energy performance comparison of three innovative HVAC systems for renovation through dynamic simulation

In this paper, dynamic simulation was used to compare the energy performance of three innovativeHVAC systems: (A) mechanical ventilation with heat recovery (MVHR) and micro heat pump, (B) exhaustventilation with exhaust air-to-water heat pump and ventilation radiators, and (C) exhaust ventilationwith air-to-water heat pump and ventilation radiators, to a reference system: (D) exhaust ventilation withair-to-water heat pump and panel radiators. System A was modelled in MATLAB Simulink and systems Band C in TRNSYS 17. The reference system was modelled in both tools, for comparison between the two.All systems were tested with a model of a renovated single family house for varying U-values, climates,infiltration and ventilation rates.It was found that A was the best system for lower heating demand, while for higher heating demandsystem B would be preferable. System C was better than the reference system, but not as good as A or B.The difference in energy consumption of the reference system was less than 2 kWh/(m2a) betweenSimulink and TRNSYS. This could be explained by the different ways of handling solar gains, but also bythe fact that the TRNSYS systems supplied slightly more than the ideal heating demand.

South Carolina/general sessions court circuits meeting benchmark : 80% of pending docket 365 days or less as of September 30, 2016

This document provides statistics on criminal and general sessions courts meeting the benchmark of 80% of pending dockets broken down by circuits and counties.