Analysis of one-pass block cipher based authenticated encryption schemes

This project analyses and evaluates the integrity assurance mechanisms used in four Authenticated Encryption schemes based on symmetric block ciphers. These schemes are all cross chaining block cipher modes that claim to provide both confidentiality and integrity assurance simultaneously, in one pass over the data. The investigations include assessing the validity of an existing forgery attack on certain schemes, applying the attack approach to other schemes and implementing the attacks to verify claimed probabilities of successful forgeries. For these schemes, the theoretical basis of the attack was developed, the attack algorithm implemented and computer simulations performed for experimental verification.

Sparse Representations for Fast, One-Shot Learning

Humans rapidly and reliably learn many kinds of regularities and generalizations. We propose a novel model of fast learning that exploits the properties of sparse representations and the constraints imposed by a plausible hardware mechanism. To demonstrate our approach we describe a computational model of acquisition in the domain of morphophonology. We encapsulate phonological information as bidirectional boolean constraint relations operating on the classical linguistic representations of speech sounds in term of distinctive features. The performance model is described as a hardware mechanism that incrementally enforces the constraints. Phonological behavior arises from the action of this mechanism. Constraints are induced from a corpus of common English nouns and verbs. The induction algorithm compiles the corpus into increasingly sophisticated constraints. The algorithm yields one-shot learning from a few examples. Our model has been implemented as a computer program. The program exhibits phonological behavior similar to that of young children. As a bonus the constraints that are acquired can be interpreted as classical linguistic rules.

An efficient one-pass method for discovering bases of recently frequent episodes over online data streams

The knowledge embedded in an online data stream is likely to change over time due to the dynamic evolution of the stream. Consequently, infrequent episode mining over an online stream, frequent episodes should be adaptively extracted from recently generated stream segments instead of the whole stream. However, almost all existing frequent episode mining approaches find episodes frequently occurring over the whole sequence. This paper proposes and investigates a new problem: online mining of recently frequent episodes over data streams. In order to meet strict requirements of stream mining such as one-scan, adaptive result update and instant result return, we choose a novel frequency metric and define a highly condensed set called the base of recently frequent episodes. We then introduce a one-pass method for mining bases of recently frequent episodes. Experimental results show that the proposed method is capable of finding bases of recently frequent episodes quickly and adaptively. The proposed method outperforms the previous approaches with the advantages of one-pass, instant result update and return, more condensed resulting sets and less space usage.

A study of actinic cheilitis treatment by two low-morbidity CO(2) laser vaporization one-pass protocols

Therapeutic approaches to chronic actinic cheilitis focus on the removal or destruction of diseased epithelium. The CO(2) laser has become an important therapeutic alternative, achieving clinical resolution in around 90% of patients. Although many laser physical parameters have been reported, some are known for their low potential for scar induction without compromising the success of the results. The aim of this clinicohistological study was to compare the therapeutic responses to two low-morbidity protocols involving a single laser pass. A total of 40 patients with chronic multicentric and microscopically proven disease were randomly submitted to two conservative CO(2) laser protocols using a bilateral comparative model. The degree of histological atypia of the epithelium was determined in 26 patients both pre- and postoperatively for both protocols. Other histological phenomena were assessed in addition to this central analysis parameter. Clinical recurrence occurred in 12.5% of patients for each protocol, together with a significant reduction in the degree of epithelial atypia (p < 0.001), which was occasionally complete. However, no difference was found between the protocols (p > 0.05). Using these morphological parameters it was not possible to determine whether postoperative epithelial atypias in part of the sample were reactive or residual in nature. A few patients may show minor postoperative lesions. Due to their potential to achieve clinical and importantly microscopic resolution, the studied protocols may be used for mild through moderate dysplastic epithelium and clinically diffuse disease.

General Regression Neuro–Fuzzy Network for Identification of Nonstationary Plants

General Regression Neuro-Fuzzy Network, which combines the properties of conventional General Regression Neural Network and Adaptive Network-based Fuzzy Inference System is proposed in this work. This network relates to so-called “memory-based networks”, which is adjusted by one-pass learning algorithm.

Parameter optimization of kernel-based one-class classifier on imbalance learning

Compared with conventional two-class learning schemes, one-class classification simply uses a single class in the classifier training phase. Applying one-class classification to learn from unbalanced data set is regarded as the recognition based learning and has shown to have the potential of achieving better performance. Similar to twoclass learning, parameter selection is a significant issue, especially when the classifier is sensitive to the parameters. For one-class learning scheme with the kernel function, such as one-class Support Vector Machine and Support Vector Data Description, besides the parameters involved in the kernel, there is another one-class specific parameter: the rejection rate v. In this paper, we proposed a general framework to involve the majority class in solving the parameter selection problem. In this framework, we first use the minority target class for training in the one-class classification stage; then we use both minority and majority class for estimating the generalization performance of the constructed classifier. This generalization performance is set as the optimization criteria. We employed the Grid search and Experiment Design search to attain various parameter settings. Experiments on UCI and Reuters text data show that the parameter optimized one-class classifiers outperform all the standard one-class learning schemes we examined.

Rainfall-runoff modeling using dynamic evolving neural fuzzy inference system with online learning

This is an open access article under the CC BY-NC-ND license.Neuro-Fuzzy Systems (NFS) are computational intelligence tools that have recently been employed in hydrological modeling. In many of the common NFS the learning algorithms used are based on batch learning where all the parameters of the fuzzy system are optimized off-line. Although these models have frequently been used, there is a criticism on such learning process as the number of rules are needed to be predefined by the user. This will reduce the flexibility of the NFS architecture while dealing with different data with different level of complexity. On the other hand, online or local learning evolves through local adjustments in the model as new data is introduced in sequence. In this study, dynamic evolving neural fuzzy inference system (DENFIS) is used in which an evolving, online clustering algorithm called the Evolving Clustering Method (ECM) is implemented. ECM is an online, maximum distance-based clustering method which is able to estimate the number of clusters in a data set and find their current centers in the input space through its fast, one-pass algorithm. The 10-minutes rainfall-runoff time series from a small (23.22 km2) tropical catchment named Sungai Kayu Ara in Selangor, Malaysia, was used in this study. Out of the 40 major events, 12 were used for training and 28 for testing. Results obtained by DENFIS were then compared with the ones obtained by physically-based rainfall-runoff model HEC-HMS and a regression model ARX. It was concluded that DENFIS results were comparable to HEC-HMS and superior to ARX model. This indicates a strong potential for DENFIS to be used in rainfall-runoff modeling.

Adding a receding horizon to Locally Weighted Regression for learning robot control

There have been notable advances in learning to control complex robotic systems using methods such as Locally Weighted Regression (LWR). In this paper we explore some potential limits of LWR for robotic applications, particularly investigating its application to systems with a long horizon of temporal dependence. We define the horizon of temporal dependence as the delay from a control input to a desired change in output. LWR alone cannot be used in a temporally dependent system to find meaningful control values from only the current state variables and output, as the relationship between the input and the current state is under-constrained. By introducing a receding horizon of the future output states of the system, we show that sufficient constraint is applied to learn good solutions through LWR. The new method, Receding Horizon Locally Weighted Regression (RH-LWR), is demonstrated through one-shot learning on a real Series Elastic Actuator controlling a pendulum.

Blended learning in medical imaging pre-clinical skills training – does it work?

Undergraduate Medical Imaging (MI)students at QUT attend their first clinical placement towards the end of semester two. Students undertake two (pre)clinical skills development units – one theory and one practical. Students gain good contextual and theoretical knowledge during these units via a blended learning model with multiple learning methods employed. Students attend theory lectures, practical sessions, tutorial sessions in both a simulated and virtual environment and also attend pre-clinical scenario based tutorial sessions. The aim of this project is to evaluate the use of blended learning in the context of 1st year Medical Imaging Radiographic Technique and its effectiveness in preparing students for their first clinical experience. It is hoped that the multiple teaching methods employed within the pre-clinical training unit at QUT builds students clinical skills prior to the real situation. A quantitative approach will be taken, evaluating via pre and post clinical placement surveys. This data will be correlated with data gained in the previous year on the effectiveness of this training approach prior to clinical placement. In 2014 59 students were surveyed prior to their clinical placement demonstrated positive benefits of using a variety of learning tools to enhance their learning. 98.31%(n=58)of students agreed or strongly agreed that the theory lectures were a useful tool to enhance their learning. This was followed closely by 97% (n=57) of the students realising the value of performing role-play simulation prior to clinical placement. Tutorial engagement was considered useful for 93.22% (n=55) whilst 88.14% (n=52) reasoned that the x-raying of phantoms in the simulated radiographic laboratory was beneficial. Self-directed learning yielded 86.44% (n=51). The virtual reality simulation software was valuable for 72.41% (n=42) of the students. Of the 4 students that disagreed or strongly disagreed with the usefulness of any tool they strongly agreed to the usefulness of a minimum of one other learning tool. The impact of the blended learning model to meet diverse student needs continues to be positive with students engaging in most offerings. Students largely prefer pre -clinical scenario based practical and tutorial sessions where 'real-world’ situations are discussed.

Learning Challenges in Biogas Production for Sustainability : An activity theoretical study of a network from a swine industry chain

This study is about the challenges of learning in the creation and implementation of new sustainable technologies. The system of biogas production in the Programme of Sustainable Swine Production (3S Programme) conducted by the Sadia food processing company in Santa Catarina State, Brazil, is used as a case example for exploring the challenges, possibilities and obstacles of learning in the use of biogas production as a way to increase the environmental sustainability of swine production. The aim is to contribute to the discussion about the possibilities of developing systems of biogas production for sustainability (BPfS). In the study I develop hypotheses concerning the central challenges and possibilities for developing systems of BPfS in three phases. First, I construct a model of the network of activities involved in the BP for sustainability in the case study. Next, I construct a) an idealised model of the historically evolved concepts of BPfS through an analysis of the development of forms of BP and b) a hypothesis of the current central contradictions within and between the activity systems involved in BP for sustainability in the case study. This hypothesis is further developed through two actual empirical analyses: an analysis of the actors senses in taking part in the system, and an analysis of the disturbance processes in the implementation and operation of the BP system in the 3S Programme. The historical analysis shows that BP for sustainability in the 3S Programme emerged as a feasible solution for the contradiction between environmental protection and concentration, intensification and specialisation in swine production. This contradiction created a threat to the supply of swine to the food processing company. In the food production activity, the contradiction was expressed as a contradiction between the desire of the company to become a sustainable company and the situation in the outsourced farms. For the swine producers the contradiction was expressed between the contradictory rules in which the market exerted pressure which pushed for continual increases in scale, specialisation and concentration to keep the production economically viable, while the environmental rules imposed a limit to this expansion. Although the observed disturbances in the biogas system seemed to be merely technical and localised within the farms, the analysis proposed that these disturbances were formed in and between the activity systems involved in the network of BPfS during the implementation. The disturbances observed could be explained by four contradictions: a) contradictions between the new, more expanded activity of sustainable swine production and the old activity, b) a contradiction between the concept of BP for carbon credits and BP for local use in the BPfS that was implemented, c) contradictions between the new UNFCCC1 methodology for applying for carbon credits and the small size of the farms, and d) between the technologies of biogas use and burning available in the market and the small size of the farms. The main finding of this study relates to the zone of proximal development (ZPD) of the BPfS in Sadia food production chain. The model is first developed as a general model of concepts of BPfS and further developed here to the specific case of the BPfS in the 3S Programme. The model is composed of two developmental dimensions: societal and functional integration. The dimension of societal integration refers to the level of integration with other activities outside the farm. At one extreme, biogas production is self-sufficient and highly independent and the products of BP are consumed within the farm, while at the other extreme BP is highly integrated in markets and networks of collaboration, and BP products are exchanged within the markets. The dimension of functional integration refers to the level of integration between products and production processes so that economies of scope can be achieved by combining several functions using the same utility. At one extreme, BP is specialised in only one product, which allows achieving economies of scale, while at the other extreme there is an integrated production in which several biogas products are produced in order to maximise the outcomes from the BP system. The analysis suggests that BP is moving towards a societal integration, towards the market and towards a functional integration in which several biogas products are combined. The model is a hypothesis to be further tested through interventions by collectively constructing the new proposed concept of BPfS. Another important contribution of this study refers to the concept of the learning challenge. Three central learning challenges for developing a sustainable system of BP in the 3S Programme were identified: 1) the development of cheaper and more practical technologies of burning and measuring the gas, as well as the reduction of costs of the process of certification, 2) the development of new ways of using biogas within farms, and 3) the creation of new local markets and networks for selling BP products. One general learning challenge is to find more varied and synergic ways of using BP products than solely for the production of carbon credits. Both the model of the ZPD of BPfS and the identified learning challenges could be used as learning tools to facilitate the development of biogas production systems. The proposed model of the ZPD could be used to analyse different types of agricultural activities that face a similar contradiction. The findings could be used in interventions to help actors to find their own expansive actions and developmental projects for change. Rather than proposing a standardised best concept of BPfS, the idea of these learning tools is to facilitate the analysis of local situations and to help actors to make their activities more sustainable.

Promoting self-regulated learning in technology enhanced learning environments : keeping a digital track of the learning process

Tese de doutoramento (co-tutela), Psicologia (Psicologia da Educação), Faculdade de Psicologia da Universidade de Lisboa, Faculdade de Psicologia e de Ciências da Educação da Universidade de Coimbra, Technial University of Darmstadt, 2014

Students’ Role in Distance Learning

1. IntroductionMuch of the support that students have in a traditional classroom is absent in a distance learning course. In the traditional classroom, the learner is together with his or her classmates and the teacher; learning is socially embedded. Students can talk to each other and may learn from each other as they go through the learning process together. They also witness the teacher’s expression of the knowledge firsthand. The class participants communicate to each other not only through their words, but also through their gestures, facial expressions and tone of voice, and the teacher can observe the students’ progress and provide guidance and feedback in an as-needed basis. Further, through the habit of meeting in a regular place at a regular time, the participants reinforce their own and each other’s commitment to the course. A distance course must somehow provide learners other kinds of supports so that the distance learner also has a sense of connection with a learning community; can benefit from interaction with peers who are going through a similar learning process; receives feedback that allows him or her to know how he or she is progressing; and is guided enough so that he or she continues to progress towards the learning objectives. This cannot be accomplished if the distance course does not simultaneously promote student autonomy, for the distance course format requires students to take greater responsibility for their own learning. This chapter presents one distance learning course that was able to address all of these goals. The English Department at Högskolan Dalarna, Sweden, participates in a distance learning program with Vietnam National University. Students enrolled in this program study half-time for two years to complete a Master’s degree in English Linguistics. The distance courses in this program all contain two types of regular class meetings: one type is student-only seminars conducted through text chat, during which students discuss and complete assignments that prepare them for the other type of class meeting, also conducted through text chat, where the teacher is present and is the one to lead the discussion of seminar issues and assignments. The inclusion of student-only seminars in the course design allows for student independence while at the same time it encourages co-operation and solidarity. The teacher-led seminars offer the advantages of a class led by an expert.In this chapter, we present chatlog data from Vietnamese students in one distance course in English linguistics, comparing the role of the student in both student-only and teacher-led seminars. We discuss how students navigate their participation roles, through computer-mediated communication (CMC), according to seminar type, and we consider the emerging role of the autonomous student in the foreign-language medium, distance learning environment. We close by considering aspects of effective design of distance learning courses from the perspective of a foreign language (FL) environment.

Study of the Geelong Local Learning and Employment Network

In common with many Western nations, Australian governments, both state and federal, have increasingly embraced network-based approaches in responding to the effects of globalisation. Since 2001, thirty one Local Learning and Employment Networks (LLEN) have been established across all areas of Victoria, Australia in line with recommendations of a Ministerial Review into Post Compulsory Education and Training Pathways. That review reported that, in the globalised context, youth in transition from schooling to independence faced persistent and severe difficulties unknown to previous generations; it also found problems were frequently concentrated in particular groups and regions. LLEN bring together the expertise and experience of local education providers, industry, community organisations, individuals and government organisations. As a result of their local decisions, collaboration and community building efforts it is intended that opportunities for young people will be enhanced. My research was conducted within an Australian Research Council Linkage Project awarded to Deakin University Faculty of Education in partnership with the Smart Geelong Region LLEN (SGR LLEN). The Linkage Project included two separate research components one of which forms my thesis: a case study of SGR LLEN. My data was generated through participant observation in SGR LLEN throughout 2004 and 2005 and through interviews, reflective writing and archival review. In undertaking my analysis and presenting my thesis I have chosen to weave a series of panels whose orientation is poststructural. This approach was based in my acceptance that all knowledge is partial and fragmentary and, accordingly, researchers need to find ways that highlight the intersections in and indeterminacy of their empirical data. The LLEN is -by its nature as a network -more than the contractual entity that gains funding from government, acts as the administrative core and occupies the LLEN office. As such I have woven firstly the formation and operational structure of the bounded entity that is SGR LLEN before weaving a series of six images that portray the unbounded LLEN as an instance-in-action. The thesis draws its theoretical inspiration from the work of Deleuze and Guattari (1987). Despite increased use of notions of networks, local decision-making and community building by governments there had been little empirical research that explored stakeholder understandings of networks and their role in community building as well as a lack of theorisation of how networks actually ‘work.’ My research addresses this lack and suggests an instituted network can function as a learning community capable of fostering systemic change in the post compulsory education training and employment sector and thereby contributing to better opportunities for young people. However the full potential of the policy is undermined by the reluctance of governments to follow through on the implications of their policies and, in particular, to confront the limiting effects of performativity at all levels.