Does gender moderate the relationship between polydrug use and sexual risk-taking among Australian secondary school students under 16 years of age?

Introduction and Aims This study examines the association of alcohol and polydrug use with risky sexual behaviour in adolescents under 16 years of age and if this association differs by gender. Design and Methods The sample consisted of 5412 secondary school students under 16 years of age from Victoria, Australia. Participants completed an anonymous and confidential survey during class time. The key measures were having had sex before legal age of consent (16 years), unprotected sex before 16 (no condom) and latent-class derived alcohol and polydrug use variables based on alcohol, tobacco, cannabis, inhalants and other illegal drug use in the past month. Results There were 7.52% and 2.55% of adolescents who reported having sex and having unprotected sex before 16 years of age, respectively. After adjusting for antisocial behaviours, peers' drug use and family and school risk factors, girls were less likely to have unprotected sex (odds ratio = 0.31, P = 0.003). However, the interaction of being female and polydrug use (odds ratio = 4.52, P = 0.004) was significant, indicating that girls who engaged in polydrug use were at higher risk of having unprotected sex. For boys, the effect of polydrug use was non-significant (odds ratio = 1.44, P = 0.310). Discussion and Conclusions For girls, polydrug use was significantly associated with unprotected sex after adjusting for a range of risk factors, and this relationship was non-significant for boys. Future prevention programs for adolescent risky sexual behaviour and polydrug use might benefit from a tailored approach to gender differences.

Software Pipelined Execution of Stream Programs on GPUs

The StreamIt programming model has been proposed to exploit parallelism in streaming applications on general purpose multi-core architectures. This model allows programmers to specify the structure of a program as a set of filters that act upon data, and a set of communication channels between them. The StreamIt graphs describe task, data and pipeline parallelism which can be exploited on modern Graphics Processing Units (GPUs), as they support abundant parallelism in hardware. In this paper, we describe the challenges in mapping StreamIt to GPUs and propose an efficient technique to software pipeline the execution of stream programs on GPUs. We formulate this problem - both scheduling and assignment of filters to processors - as an efficient Integer Linear Program (ILP), which is then solved using ILP solvers. We also describe a novel buffer layout technique for GPUs which facilitates exploiting the high memory bandwidth available in GPUs. The proposed scheduling utilizes both the scalar units in GPU, to exploit data parallelism, and multiprocessors, to exploit task and pipelin parallelism. Further it takes into consideration the synchronization and bandwidth limitations of GPUs, and yields speedups between 1.87X and 36.83X over a single threaded CPU.

Youth programs in remote Indigenous communities: Context matters

A diversity of programs oriented to young people seek to develop their capacities and their connection to the communities in which they live. Some focus on ameliorating a particular issue or ‘deficit’ whilst others, such as sporting, recreation and youth groups are more grounded in the community. This article reports a qualitative study undertaken in three remote Indigenous communities in Central Australia. Sixty interviews were conducted with a range of stakeholders involved in a diversity of youth programs. A range of critical challenges for and characteristics of remote Indigenous youth programs are identified if such programs are to be ‘fit for context’. ‘Youth centred-context specific’ provides a positive frame for the delivery of youth programs in remote Central Australia, encouraging an explicit focus on program logic; program content and processes; and relational, temporal, and, spatial aspects of the practice context. These provide lenses with which youth program planning and delivery may be enhanced in remote communities. Culturally safe service planning and delivery suggests locally determined processes for decision-making and community ownership. In some cases, this may mean a community preference for all ages to access the service to engage in culturally relevant activities. Where activities are targeted at young people, yet open to and inclusive of all ages, they provide a medium for cross-generational interaction that requires a high degree of flexibility on the part of staff and funding programs. Although the findings are focused in Central Australia, they may be relevant to similar contexts elsewhere.

Relationship Drivers in Provider - Consumer Relationships. Empirical Studies of Customer Loyalty Programs (första upplagan slutsåld / first edition sold out, 'print on demand' 60 €)

The study addressed a phenomenon that has become common marketing practice, customer loyalty programs. Although a common type of consumer relationship, there is limited knowledge of its nature. The purpose of the study was to create structured understanding of the nature of customer relationships from both the provider’s and the consumer’s viewpoints by studying relationship drivers and proposing the concept of relational motivation as a provider of a common framework for the analysis of these views. The theoretical exploration focused on reasons for engaging in customer relationships for both the consumer and the provider. The themes of buying behaviour, industrial and network marketing and relationship marketing, as well as the concepts of a customer relationship, customer loyalty, relationship conditions, relational benefits, bonds and commitment were explored and combined in a new way. Concepts from the study of business-to-business relationships were brought over and their power in explaining the nature of consumer relationships examined. The study provided a comprehensive picture of loyalty programs, which is an important contribution to the academic as well as the managerial discussions. The consumer study provided deep insights into the nature of customer relationships. The study provides a new frame of reference to support the existing concepts of loyalty and commitment with the introduction of the relationship driver and relational motivation concepts. The result is a novel view of the nature of customer relationships that creates new understanding of the forces leading to loyal behaviour and commitment. The study concludes with managerial implications.

Fuzzy Clustering Based Ad Recommendation for TV Programs

Advertisements(Ads) are the main revenue earner for Television (TV) broadcasters. As TV reaches a large audience, it acts as the best media for advertisements of products and services. With the emergence of digital TV, it is important for the broadcasters to provide an intelligent service according to the various dimensions like program features, ad features, viewers’ interest and sponsors’ preference. We present an automatic ad recommendation algorithm that selects a set of ads by considering these dimensions and semantically match them with programs. Features of the ad video are captured interms of annotations and they are grouped into number of predefined semantic categories by using a categorization technique. Fuzzy categorical data clustering technique is applied on categorized data for selecting better suited ads for a particular program. Since the same ad can be recommended for more than one program depending upon multiple parameters, fuzzy clustering acts as the best suited method for ad recommendation. The relative fuzzy score called “degree of membership” calculated for each ad indicates the membership of a particular ad to different program clusters. Subjective evaluation of the algorithm is done by 10 different people and rated with a high success score.

Petri net based performance modeling for effective DVFS for multithreaded programs

Dynamic Voltage and Frequency Scaling (DVFS) is a very effective tool for designing trade-offs between energy and performance. In this paper, we use a formal Petri net based program performance model that directly captures both the application and system properties, to find energy efficient DVFS settings for CMP systems, that satisfy a given performance constraint, for SPMD multithreaded programs. Experimental evaluation shows that we achieve significant energy savings, while meeting the performance constraints.

Evaluation of dynamic voltage and frequency scaling for stream programs

Dynamic Voltage and Frequency Scaling (DVFS) offers a huge potential for designing trade-offs involving energy, power, temperature and performance of computing systems. In this paper, we evaluate three different DVFS schemes - our enhancement of a Petri net performance model based DVFS method for sequential programs to stream programs, a simple profile based Linear Scaling method, and an existing hardware based DVFS method for multithreaded applications - using multithreaded stream applications, in a full system Chip Multiprocessor (CMP) simulator. From our evaluation, we find that the software based methods achieve significant Energy/Throughput2(ET−2) improvements. The hardware based scheme degrades performance heavily and suffers ET−2 loss. Our results indicate that the simple profile based scheme achieves the benefits of the complex Petri net based scheme for stream programs, and present a strong case for the need for independent voltage/frequency control for different cores of CMPs, which is lacking in most of the state-of-the-art CMPs. This is in contrast to the conclusions of a recent evaluation of per-core DVFS schemes for multithreaded applications for CMPs.

Dataflow analysis for data-race free programs

Memory models for shared-memory concurrent programming languages typically guarantee sequential consistency (SC) semantics for datarace-free (DRF) programs, while providing very weak or no guarantees for non-DRF programs. In effect programmers are expected to write only DRF programs, which are then executed with SC semantics. With this in mind, we propose a novel scalable solution for dataflow analysis of concurrent programs, which is proved to be sound for DRF programs with SC semantics. We use the synchronization structure of the program to propagate dataflow information among threads without requiring to consider all interleavings explicitly. Given a dataflow analysis that is sound for sequential programs and meets certain criteria, our technique automatically converts it to an analysis for concurrent programs.

TCP: thread contention predictor for parallel programs

With proliferation of chip multicores (CMPs) on desktops and embedded platforms, multi-threaded programs have become ubiquitous. Existence of multiple threads may cause resource contention, such as, in on-chip shared cache and interconnects, depending upon how they access resources. Hence, we propose a tool - Thread Contention Predictor (TCP) to help quantify the number of threads sharing data and their sharing pattern. We demonstrate its use to predict a more profitable shared, last level on-chip cache (LLC) access policy on CMPs. Our cache configuration predictor is 2.2 times faster compared to the cycle-accurate simulations. We also demonstrate its use for identifying hot data structures in a program which may cause performance degradation due to false data sharing. We fix layout of such data structures and show up-to 10% and 18% improvement in execution time and energy-delay product (EDP), respectively.

Static analysis for checking data format compatibility of programs

Large software systems are developed by composing multiple programs. If the programs manip-ulate and exchange complex data, such as network packets or files, it is essential to establish that they follow compatible data formats. Most of the complexity of data formats is associated with the headers. In this paper, we address compatibility of programs operating over headers of network packets, files, images, etc. As format specifications are rarely available, we infer the format associated with headers by a program as a set of guarded layouts. In terms of these formats, we define and check compatibility of (a) producer-consumer programs and (b) different versions of producer (or consumer) programs. A compatible producer-consumer pair is free of type mismatches and logical incompatibilities such as the consumer rejecting valid outputs gen-erated by the producer. A backward compatible producer (resp. consumer) is guaranteed to be compatible with consumers (resp. producers) that were compatible with its older version. With our prototype tool, we identified 5 known bugs and 1 potential bug in (a) sender-receiver modules of Linux network drivers of 3 vendors and (b) different versions of a TIFF image library.

Precise Slicing in Imperative Programs via Term-Rewriting and Abstract Interpretation

We propose a new approach for producing precise constrained slices of programs in a language such as C. We build upon a previous approach for this problem, which is based on term-rewriting, which primarily targets loop-free fragments and is fully precise in this setting. We incorporate abstract interpretation into term-rewriting, using a given arbitrary abstract lattice, resulting in a novel technique for slicing loops whose precision is linked to the power of the given abstract lattice. We address pointers in a first-class manner, including when they are used within loops to traverse and update recursive data structures. Finally, we illustrate the comparative precision of our slices over those of previous approaches using representative examples.

Compiler/Runtime Framework for Dynamic Dataflow Parallelization of Tiled Programs

Task-parallel languages are increasingly popular. Many of them provide expressive mechanisms for intertask synchronization. For example, OpenMP 4.0 will integrate data-driven execution semantics derived from the StarSs research language. Compared to the more restrictive data-parallel and fork-join concurrency models, the advanced features being introduced into task-parallelmodels in turn enable improved scalability through load balancing, memory latency hiding, mitigation of the pressure on memory bandwidth, and, as a side effect, reduced power consumption. In this article, we develop a systematic approach to compile loop nests into concurrent, dynamically constructed graphs of dependent tasks. We propose a simple and effective heuristic that selects the most profitable parallelization idiom for every dependence type and communication pattern. This heuristic enables the extraction of interband parallelism (cross-barrier parallelism) in a number of numerical computations that range from linear algebra to structured grids and image processing. The proposed static analysis and code generation alleviates the burden of a full-blown dependence resolver to track the readiness of tasks at runtime. We evaluate our approach and algorithms in the PPCG compiler, targeting OpenStream, a representative dataflow task-parallel language with explicit intertask dependences and a lightweight runtime. Experimental results demonstrate the effectiveness of the approach.