Mining discriminative Itemsets in data streams

This paper presents a single pass algorithm for mining discriminative Itemsets in data streams using a novel data structure and the tilted-time window model. Discriminative Itemsets are defined as Itemsets that are frequent in one data stream and their frequency in that stream is much higher than the rest of the streams in the dataset. In order to deal with the data structure size, we propose a pruning process that results in the compact tree structure containing discriminative Itemsets. Empirical analysis shows the sound time and space complexity of the proposed method.

Advances in the science of objective physical activity monitoring : 3rd International Conference on Ambulatory Monitoring of Physical Activity and Movement

Editorial: This theme issue of BJSM presents key papers from the 3rd International Conference on Ambulatory Monitoring of Physical Activity and Movement (ICAMPAM). The July 2013 conference was hosted by the University of Massachusetts and was attended by researchers, clinicians, students and technology vendors for North America, Europe, Australasia and Asia...

Visual narratives and counter-narratives in aged care : Centring the participant as photographer in social science research

As detailed by a number of scholars (Emmison & Smith, 2000, 2012; Harrison, 1996, 2002, 2004), photographs and the process of photographing can provide fertile ground for sociological investigation. Examining the production of photography can tell us much about inclusion/omission and power/knowledge in a variety of social settings. Recently, some researchers have begun to utilise the participatory action research methodology, PhotoVoice, where people take and share photographs as a means of communicating and advocating on a specific topic. While medical sociologists have used PhotoVoice to communicate the impacts of disease in vulnerable populations (eg Burles, 2010), little social research has been done that combines PhotoVoice and older persons. This is interesting given the world’s population is ageing and the general lack of research that examines what daily life is like for older people living in aged care (Timonen & O’Dwyer, 2009). In response, a recent project tracked 10 participants who recently transitioned into living in residential aged care (RAC). The project combined the use of PhotoVoice methodology with repeated in-depth interviews. Residents were asked to orally and visually describe the positives and negative aspects of their daily lives. In the first instance, they shared the use of a RAC owned camera and later had the opportunity to access a camera for their sole use. Photographic analysis emphasised the value of centring the participant as an autonomous photographer in social research. In the photographs captured on a shared use camera, the photographs tended to depict predominately positive life stories (e.g. weekly morning tea outings, social activities). In comparison, the photographs captured on the sole use camera also described intimate but everyday activities, spaces, objects and people that frequented in their daily lives. Shifting the responsibility of the camera and photography solely to the participants resulted in the residents disrupting conventions of ‘suitable’ subject matter to photograph (Harrison, 2004) and in doing so, provided a much richer insight into what daily life is like in aged care.

“I was proud of myself that I didn’t give up and I did it”: Experiences of pride and triumph in learning science

The role that specific emotions, such as pride and triumph, play during instruction in science education is an under-researched field of study. Emotions are recognized as central to learning yet little is known about the way in which they are produced in naturalistic settings, how emotions relate to classroom learning during interactions, and what antecedent factors are associated with emotional experiences during instruction. Data sources for the study include emotion diaries, student written artifacts, video recordings of class interactions, and interviews. Emotions produced in the moment during classroom interactions are analyzed from video data and audio data through a novel theoretical framework related to the sociology of human emotions. These direct observations are compared with students’ recollected emotional experiences reported through emotion diaries and interviews. The study establishes links between pride and triumph within classroom interactions and instructional tasks during learning episodes in a naturalistic setting. We discuss particular classroom activities that are associated with justified feelings of pride and triumph. More specifically, classroom events associated with these emotions were related to understanding science concepts, social interactions, and achieving success on challenging tasks.

Hierarchical deterministic Bitcoin wallets that tolerate key leakage (short paper)

A Bitcoin wallet is a set of private keys known to a user and which allow that user to spend any Bitcoin associated with those keys. In a hierarchical deterministic (HD) wallet, child private keys are generated pseudorandomly from a master private key, and the corresponding child public keys can be generated by anyone with knowledge of the master public key. These wallets have several interesting applications including Internet retail, trustless audit, and a treasurer allocating funds among departments. A specification of HD wallets has even been accepted as Bitcoin standard BIP32. Unfortunately, in all existing HD wallets---including BIP32 wallets---an attacker can easily recover the master private key given the master public key and any child private key. This vulnerability precludes use cases such as a combined treasurer-auditor, and some in the Bitcoin community have suspected that this vulnerability cannot be avoided. We propose a new HD wallet that is not subject to this vulnerability. Our HD wallet can tolerate the leakage of up to m private keys with a master public key size of O(m). We prove that breaking our HD wallet is at least as hard as the so-called "one more" discrete logarithm problem.

Modelling ciphersuite and version negotiation in the TLS protocol

Real-world cryptographic protocols such as the widely used Transport Layer Security (TLS) protocol support many different combinations of cryptographic algorithms (called ciphersuites) and simultaneously support different versions. Recent advances in provable security have shown that most modern TLS ciphersuites are secure authenticated and confidential channel establishment (ACCE) protocols, but these analyses generally focus on single ciphersuites in isolation. In this paper we extend the ACCE model to cover protocols with many different sub-protocols, capturing both multiple ciphersuites and multiple versions, and define a security notion for secure negotiation of the optimal sub-protocol. We give a generic theorem that shows how secure negotiation follows, with some additional conditions, from the authentication property of secure ACCE protocols. Using this framework, we analyse the security of ciphersuite and three variants of version negotiation in TLS, including a recently proposed mechanism for detecting fallback attacks.

‘Blind Faith’. An experiment with narrative agency in game design

This paper reports on the current field of narrative-based game design through case study analysis with a particular focus on balancing high narrative agency with low production resources.

Application of simulated annealing to data distribution for all-to-all comparison problems in homogeneous systems

Distributed systems are widely used for solving large-scale and data-intensive computing problems, including all-to-all comparison (ATAC) problems. However, when used for ATAC problems, existing computational frameworks such as Hadoop focus on load balancing for allocating comparison tasks, without careful consideration of data distribution and storage usage. While Hadoop-based solutions provide users with simplicity of implementation, their inherent MapReduce computing pattern does not match the ATAC pattern. This leads to load imbalances and poor data locality when Hadoop's data distribution strategy is used for ATAC problems. Here we present a data distribution strategy which considers data locality, load balancing and storage savings for ATAC computing problems in homogeneous distributed systems. A simulated annealing algorithm is developed for data distribution and task scheduling. Experimental results show a significant performance improvement for our approach over Hadoop-based solutions.

Using genetic algorithm in profile-based assignment of applications to virtual machines for greener data centers

The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.

A penalty-based genetic algorithm for the migration cost-aware virtual machine placement problem in cloud data centers

In the past few years, the virtual machine (VM) placement problem has been studied intensively and many algorithms for the VM placement problem have been proposed. However, those proposed VM placement algorithms have not been widely used in today's cloud data centers as they do not consider the migration cost from current VM placement to the new optimal VM placement. As a result, the gain from optimizing VM placement may be less than the loss of the migration cost from current VM placement to the new VM placement. To address this issue, this paper presents a penalty-based genetic algorithm (GA) for the VM placement problem that considers the migration cost in addition to the energy-consumption of the new VM placement and the total inter-VM traffic flow in the new VM placement. The GA has been implemented and evaluated by experiments, and the experimental results show that the GA outperforms two well known algorithms for the VM placement problem.

A Strength Pareto Evolutionary Algorithm for live migration of multiple interdependent virtual machines in data centers

Although live VM migration has been intensively studied, the problem of live migration of multiple interdependent VMs has hardly been investigated. The most important problem in the live migration of multiple interdependent VMs is how to schedule VM migrations as the schedule will directly affect the total migration time and the total downtime of those VMs. Aiming at minimizing both the total migration time and the total downtime simultaneously, this paper presents a Strength Pareto Evolutionary Algorithm 2 (SPEA2) for the multi-VM migration scheduling problem. The SPEA2 has been evaluated by experiments, and the experimental results show that the SPEA2 can generate a set of VM migration schedules with a shorter total migration time and a shorter total downtime than an existing genetic algorithm, namely Random Key Genetic Algorithm (RKGA). This paper also studies the scalability of the SPEA2.

Structure matters: Adoption of structured classification Approach in the context of cognitive presence classification

Within online learning communities, receiving timely and meaningful insights into the quality of learning activities is an important part of an effective educational experience. Commonly adopted methods – such as the Community of Inquiry framework – rely on manual coding of online discussion transcripts, which is a costly and time consuming process. There are several efforts underway to enable the automated classification of online discussion messages using supervised machine learning, which would enable the real-time analysis of interactions occurring within online learning communities. This paper investigates the importance of incorporating features that utilise the structure of on-line discussions for the classification of "cognitive presence" – the central dimension of the Community of Inquiry framework focusing on the quality of students' critical thinking within online learning communities. We implemented a Conditional Random Field classification solution, which incorporates structural features that may be useful in increasing classification performance over other implementations. Our approach leads to an improvement in classification accuracy of 5.8% over current existing techniques when tested on the same dataset, with a precision and recall of 0.630 and 0.504 respectively.

Engaging elementary students in learning science: An analysis of classroom dialogue

Research over a long period of time has continued to demonstrate problems in the teaching of science in school. In addition, declining levels of participation and interest in science and related fields have been reported from many particularly western countries. Among the strategies suggested is the recruitment of professional scientists and technologists either at the graduate level or advanced career level to change career and teach. In this study, we analysed how one beginning middle primary teacher engaged with students to support their science learning by establishing rich classroom discussions. We followed his evolving teaching expertise over three years focussing on his communicative practices informed by socio-cultural theory. His practices exemplified a non-interactive dialogical communicative approach where ideas were readily discussed but were concentrated on the class acquiring acceptable scientific understandings. His focus on the language of science was a significant aspect of his practice and one that emerged from his professional background. The study affirms the theoretical frameworks proposed by Mortimer and Scott (2003) highlighting how dialogue contributes to heightened student interest in science.

Approximation algorithm for maximum independent set in planar traingle-free graphs

The maximum independent set problem is NP-complete even when restricted to planar graphs, cubic planar graphs or triangle free graphs. The problem of finding an absolute approximation still remains NP-complete. Various polynomial time approximation algorithms, that guarantee a fixed worst case ratio between the independent set size obtained to the maximum independent set size, in planar graphs have been proposed. We present in this paper a simple and efficient, O(|V|) algorithm that guarantees a ratio 1/2, for planar triangle free graphs. The algorithm differs completely from other approaches, in that, it collects groups of independent vertices at a time. Certain bounds we obtain in this paper relate to some interesting questions in the theory of extremal graphs.