Lightweight Internet Traffic Classification - A Subject Based Solution with Word Embeddings

Internet traffic classification is a relevant and mature research field, anyway of growing importance and with still open technical challenges, also due to the pervasive presence of Internet-connected devices into everyday life. We claim the need for innovative traffic classification solutions capable of being lightweight, of adopting a domain-based approach, of not only concentrating on application-level protocol categorization but also classifying Internet traffic by subject. To this purpose, this paper originally proposes a classification solution that leverages domain name information extracted from IPFIX summaries, DNS logs, and DHCP leases, with the possibility to be applied to any kind of traffic. Our proposed solution is based on an extension of Word2vec unsupervised learning techniques running on a specialized Apache Spark cluster. In particular, learning techniques are leveraged to generate word-embeddings from a mixed dataset composed by domain names and natural language corpuses in a lightweight way and with general applicability. The paper also reports lessons learnt from our implementation and deployment experience that demonstrates that our solution can process 5500 IPFIX summaries per second on an Apache Spark cluster with 1 slave instance in Amazon EC2 at a cost of $ 3860 year. Reported experimental results about Precision, Recall, F-Measure, Accuracy, and Cohen's Kappa show the feasibility and effectiveness of the proposal. The experiments prove that words contained in domain names do have a relation with the kind of traffic directed towards them, therefore using specifically trained word embeddings we are able to classify them in customizable categories. We also show that training word embeddings on larger natural language corpuses leads improvements in terms of precision up to 180%.

Optimized CUDA-Based PDE Solver for Reaction Diffusion Systems on Arbitrary Surfaces

Partial differential equation (PDE) solvers are commonly employed to study and characterize the parameter space for reaction-diffusion (RD) systems while investigating biological pattern formation. Increasingly, biologists wish to perform such studies with arbitrary surfaces representing ‘real’ 3D geometries for better insights. In this paper, we present a highly optimized CUDA-based solver for RD equations on triangulated meshes in 3D. We demonstrate our solver using a chemotactic model that can be used to study snakeskin pigmentation, for example. We employ a finite element based approach to perform explicit Euler time integrations. We compare our approach to a naive GPU implementation and provide an in-depth performance analysis, demonstrating the significant speedup afforded by our optimizations. The optimization strategies that we exploit could be generalized to other mesh based processing applications with PDE simulations.

Value Assessment of Orphan Drugs and Treatments for Rare Diseases

Thesis (Master's)--University of Washington, 2016-06

Meaning-based quality-of-life measurement: A way forward in conceptualizing and measuring client outcomes?

Despite current imperatives to measure client outcomes, social workers have expressed frustration with the ability of traditional forms of quantitative methods to engage with complexity, individuality and meaning. This paper argues that the inclusion of a meaning-based as opposed to a function-based approach to quality of life (QOL) may offer a quantitative means of measurement that is congruent with social-work values and practice.

Improving learning in undergraduate control engineering courses using context-based learning models

Control Engineering is an essential part of university electrical engineering education. Normally, a control course requires considerable mathematical as well as engineering knowledge and is consequently regarded as a difficult course by many undergraduate students. From the academic point of view, how to help the students to improve their learning of the control engineering knowledge is therefore an important task which requires careful planning and innovative teaching methods. Traditionally, the didactic teaching approach has been used to teach the students the concepts needed to solve control problems. This approach is commonly adopted in many mathematics intensive courses; however it generally lacks reflection from the students to improve their learning. This paper addresses the practice of action learning and context-based learning models in teaching university control courses. This context-based approach has been practised in teaching several control engineering courses in a university with promising results, particularly in view of student learning performances.

Pattern-based phylogenetic distance estimation and tree reconstruction

We have developed an alignment-free method that calculates phylogenetic distances using a maximum-likelihood approach for a model of sequence change on patterns that are discovered in unaligned sequences. To evaluate the phylogenetic accuracy of our method, and to conduct a comprehensive comparison of existing alignment-free methods (freely available as Python package decaf+py at http://www.bioinformatics.org.au), we have created a data set of reference trees covering a wide range of phylogenetic distances. Amino acid sequences were evolved along the trees and input to the tested methods; from their calculated distances we infered trees whose topologies we compared to the reference trees. We find our pattern-based method statistically superior to all other tested alignment-free methods. We also demonstrate the general advantage of alignment-free methods over an approach based on automated alignments when sequences violate the assumption of collinearity. Similarly, we compare methods on empirical data from an existing alignment benchmark set that we used to derive reference distances and trees. Our pattern-based approach yields distances that show a linear relationship to reference distances over a substantially longer range than other alignment-free methods. The pattern-based approach outperforms alignment-free methods and its phylogenetic accuracy is statistically indistinguishable from alignment-based distances.

Applying a disciplined approach to the development of a context-aware communication application

Pervasive computing applications must be engineered to provide unprecedented levels of flexibility in order to reconfigure and adapt in response to changes in computing resources and user requirements. To meet these challenges, appropriate software engineering abstractions and infrastructure are required as a platform on which to build adaptive applications. In this paper, we demonstrate the use of a disciplined, model-based approach to engineer a context-aware Session Initiation Protocol (SIP) based communication application. This disciplined approach builds on our previously developed conceptual models and infrastructural components, which enable the description, acquisition, management and exploitation of arbitrary types of context and user preference information to enable adaptation to context changes

Chaos Theory as an Approach to Understanding MICE in Time of Crisis

MICE (meetings, incentives, conventions, and exhibitions), has generated high foreign exchange revenue for the economy worldwide. In Thailand, MICE tourists are recognized as ‘quality’ visitors, mainly because of their high-spending potential. Having said that, Thailand’s MICE sector has been influenced by a number of crises following September 11, 2001. Consequently, professionals in the MICE sector must be prepared to deal with such complex phenomena of crisis that might happen in the future. While a number of researches have examined the complexity of crises in the tourism context, there has been little focus on such issues in the MICE sector. As chaos theory provides a particularly good model for crisis situations, it is the aim of this paper to propose a chaos theory-based approach to the understanding of complex and chaotic system of the MICE sector in time of crisis.

Monitoring the condition of savanna riparian zones in Northern Australia using high spatial resolution imagery and a field based rapid assessment method

Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone condition. The objective of this work was to compare the Tropical Rapid Appraisal of Riparian Condition (TRARC) method to a satellite image based approach. TRARC was developed for rapid assessment of the environmental condition of savanna riparian zones. The comparison assessed mapping accuracy, representativeness of TRARC assessment, cost-effectiveness, and suitability for multi-temporal analysis. Two multi-spectral QuickBird images captured in 2004 and 2005 and coincident field data covering sections of the Daly River in the Northern Territory, Australia were used in this work. Both field and image data were processed to map riparian health indicators (RHIs) including percentage canopy cover, organic litter, canopy continuity, stream bank stability, and extent of tree clearing. Spectral vegetation indices, image segmentation and supervised classification were used to produce RHI maps. QuickBird image data were used to examine if the spatial distribution of TRARC transects provided a representative sample of ground based RHI measurements. Results showed that TRARC transects were required to cover at least 3% of the study area to obtain a representative sample. The mapping accuracy and costs of the image based approach were compared to those of the ground based TRARC approach. Results proved that TRARC was more cost-effective at smaller scales (1-100km), while image based assessment becomes more feasible at regional scales (100-1000km). Finally, the ability to use both the image and field based approaches for multi-temporal analysis of RHIs was assessed. Change detection analysis demonstrated that image data can provide detailed information on gradual change, while the TRARC method was only able to identify more gross scale changes. In conclusion, results from both methods were considered to complement each other if used at appropriate spatial scales.

A strategy-as-practice approach to strategy research and education

This conclusion to the Dialog proposes a strategy-as-practice based approach to bringing strategy research and education closer to practice. Strategy-as-practice rejects the choice, proposed in the previous articles, between theory and practice. The authors argue for strategy research based rigorously on sociological theories of practice. Such research complements the parsimony and generalizability of economics-driven theory, extending strategy research to incorporate the messy realities of doing strategy in practice, with a view to developing theory that is high in accuracy. The authors suggest that practice-based research can also inform strategy teaching by providing students with rich case studies of strategy work as actually practiced, analyzed through such sociological lenses as ethnomethodology, dramaturgy, and institutional theory. Strategy-as-practice research does not aim to give students parsimonious models for analysis or expose them to cases of best practice but rather to help them develop practical wisdom through a better understanding of strategy in practice.

Antecedents and consequences of service quality in consumer evaluation of self-service internet technologies

Advances in technology coupled with increasing labour costs have caused service firms to explore self-service delivery options. Although some studies have focused on self-service and use of technology in service delivery, few have explored the role of service quality in consumer evaluation of technology-based self-service options. By integrating and extending the self-service quality framework the service evaluation model and the Technology Acceptance Model the authors address this emerging issue by empirically testing a comprehensive model that captures the antecedents and consequences of perceived service quality to predict continued customer interaction in the technology-based self-service context of Internet banking. Important service evaluation constructs like perceived risk, perceived value and perceived satisfaction are modelled in this framework. The results show that perceived control has the strongest influence on service quality evaluations. Perceived speed of delivery, reliability and enjoyment also have a significant impact on service quality perceptions. The study also found that even though perceived service quality, perceived risk and satisfaction are important predictors of continued interaction, perceived customer value plays a pivotal role in influencing continued interaction.

School outcomes:sharing the responsibility between pupil and school

This paper uses a Data Envelopment Analysis based approach to decompose pupil under-attainment into that attributable to the school the pupil attends and that attributable to the pupil. The approach measures pupil attainment in terms of value added. Data on over 6700 A-level pupils from 122 English schools have been analysed. The results suggest that at current levels of school effectiveness a pupil's own application accounts for the major part of any under-attainment, though schools also have scope to improve their effectiveness.The approach also makes it possible to identify target attainment levels a pupil could be set and the extent to which the attainment of those targets necessitates an improvement in the effectiveness of the school the pupil attends and in the pupil's own efforts.

Do many hands make light work? How to overcome social loafing and gain motivation in work teams

Purpose – The purpose of this paper is to challenge the assumption that process losses of individuals working in teams are unavoidable. The paper aims to challenge this assumption on the basis of social identity theory and recent research. Design/methodology/approach – The approach adopted in this paper is to review the mainstream literature providing strong evidence for motivation problems of individuals working in groups. Based on more recent literature, innovative ways to overcome these problems are discussed. Findings – A social identity-based analysis and recent findings summarized in this paper show that social loafing can be overcome and that even motivation gains in group work can be expected when groups are important for the individual group members' self-concepts. Practical implications – The paper provides human resource professionals and front-line managers with suggestions as to how individual motivation and performance might be increased when working in teams. Originality/value – The paper contributes to the literature by challenging the existing approach to reducing social loafing, i.e. individualizing workers as much as possible, and proposes a team-based approach instead to overcome motivation problems.

A case study on services upgrading prediction

Customer Base Analysis is perhaps the first stage of analysis in customer value, aiming to predict purchase frequency and customer lifecycle. An important part of the customer purchase frequency and its retention has to do with the service upgrade. Many models have tried to predict purchase frequency as well as upgrading. The comparison of these models seems important to provide academics with a picture of the current situation. The purpose of this research is to evaluate how models can predict service upgrade among a customer database of an online DVD rental company and suggest an alternative based on data mining techniques and data on historical transactions.

Shareholder or stakeholder management:strategies for performance optimisation

This paper is based upon the findings of a CIMA research project into the way which corporate performance is affected by the performance measurement system adopted. It compares and contrasts the techniques in use in a sample of large companies that use a variety of techniques. We have classified these techniques into 3 types: • Value based management techniques • Stakeholder management techniques • Traditional accounting techniques. The analysis traces the interactions between corporate objectives, decision making criteria, performance measurement systems, and executive incentive schemes in order to develop an understanding of the effects of such techniques upon corporate performance. This paper seeks to provide some answers to the following two questions: • What approach leads to superior performance for a firm? • What is different between these approaches when they are used in practice, as distinct from theory? In doing so we have drawn upon both contingency theory and sociobiology theory to develop a framework for understanding the relationship between the choke of performance measurement system and the resulting performance.